{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u3Zq5VrfiDqB"
      },
      "source": [
        "##### Copyright 2018 The TensorFlow Authors.\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3jTEqPzFiHQ0"
      },
      "outputs": [],
      "source": [
        "#@title Licensed under the Apache License, Version 2.0 (the \"License\"); { display-mode: \"form\" }\n",
        "# you may not use this file except in compliance with the License.\n",
        "# You may obtain a copy of the License at\n",
        "#\n",
        "# https://www.apache.org/licenses/LICENSE-2.0\n",
        "#\n",
        "# Unless required by applicable law or agreed to in writing, software\n",
        "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "# See the License for the specific language governing permissions and\n",
        "# limitations under the License."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x97n3SaNmNpB"
      },
      "source": [
        "# Fitting Generalized Linear Mixed-effects Models Using Variational Inference\n",
        "\n",
        "\u003ctable class=\"tfo-notebook-buttons\" align=\"left\"\u003e\n",
        "  \u003ctd\u003e\n",
        "    \u003ca target=\"_blank\" href=\"https://www.tensorflow.org/probability/examples/Linear_Mixed_Effects_Model_Variational_Inference\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/tf_logo_32px.png\" /\u003eView on TensorFlow.org\u003c/a\u003e\n",
        "  \u003c/td\u003e\n",
        "  \u003ctd\u003e\n",
        "    \u003ca target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/probability/blob/master/tensorflow_probability/examples/jupyter_notebooks/Linear_Mixed_Effects_Model_Variational_Inference.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" /\u003eRun in Google Colab\u003c/a\u003e\n",
        "  \u003c/td\u003e\n",
        "  \u003ctd\u003e\n",
        "    \u003ca target=\"_blank\" href=\"https://github.com/tensorflow/probability/blob/master/tensorflow_probability/examples/jupyter_notebooks/Linear_Mixed_Effects_Model_Variational_Inference.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" /\u003eView source on GitHub\u003c/a\u003e\n",
        "  \u003c/td\u003e\n",
        "  \u003ctd\u003e\n",
        "    \u003ca href=\"https://storage.googleapis.com/tensorflow_docs/probability/examples/jupyter_notebooks/Linear_Mixed_Effects_Model_Variational_Inference.ipynb\"\u003e\u003cimg src=\"https://www.tensorflow.org/images/download_logo_32px.png\" /\u003eDownload notebook\u003c/a\u003e\n",
        "  \u003c/td\u003e\n",
        "\u003c/table\u003e"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yPby2hWGS651"
      },
      "outputs": [],
      "source": [
        "#@title Install { display-mode: \"form\" }\n",
        "TF_Installation = 'System' #@param ['TF Nightly', 'TF Stable', 'System']\n",
        "\n",
        "if TF_Installation == 'TF Nightly':\n",
        "  !pip install -q --upgrade tf-nightly\n",
        "  print('Installation of `tf-nightly` complete.')\n",
        "elif TF_Installation == 'TF Stable':\n",
        "  !pip install -q --upgrade tensorflow\n",
        "  print('Installation of `tensorflow` complete.')\n",
        "elif TF_Installation == 'System':\n",
        "  pass\n",
        "else:\n",
        "  raise ValueError('Selection Error: Please select a valid '\n",
        "                   'installation option.')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ZKFMx9zmTBbd"
      },
      "outputs": [],
      "source": [
        "#@title Install { display-mode: \"form\" }\n",
        "TFP_Installation = \"System\" #@param [\"Nightly\", \"Stable\", \"System\"]\n",
        "\n",
        "if TFP_Installation == \"Nightly\":\n",
        "  !pip install -q tfp-nightly\n",
        "  print(\"Installation of `tfp-nightly` complete.\")\n",
        "elif TFP_Installation == \"Stable\":\n",
        "  !pip install -q --upgrade tensorflow-probability\n",
        "  print(\"Installation of `tensorflow-probability` complete.\")\n",
        "elif TFP_Installation == \"System\":\n",
        "  pass\n",
        "else:\n",
        "  raise ValueError(\"Selection Error: Please select a valid \"\n",
        "                   \"installation option.\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0GVst7yy6Aww"
      },
      "source": [
        "## Abstract\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lt4RS9whJhQh"
      },
      "source": [
        "\n",
        "In this colab we demonstrate how to fit a generalized linear mixed-effects model using variational inference in TensorFlow Probability.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0-lfIBVAzi7D"
      },
      "source": [
        "## Model Family"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ljSRsKrXwqb6"
      },
      "source": [
        "[Generalized linear mixed-effect models](https://en.wikipedia.org/wiki/Generalized_linear_mixed_model) (GLMM) are similar to [generalized linear models](https://en.wikipedia.org/wiki/Generalized_linear_model) (GLM) except that they incorporate a sample specific noise into the predicted linear response.  This is useful in part because it allows rarely seen features to share information with more commonly seen features.\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H-B38entvltq"
      },
      "source": [
        "As a generative process, a Generalized Linear Mixed-effects Model (GLMM) is characterized by:\n",
        "\n",
        "$$\n",
        "\\begin{align}\n",
        "\\text{for } \u0026 r = 1\\ldots R:  \\hspace{2.45cm}\\text{# for each random-effect group}\\\\\n",
        " \u0026\\begin{aligned}\n",
        "  \\text{for } \u0026c = 1\\ldots |C_r|:  \\hspace{1.3cm}\\text{# for each category (\"level\") of group $r$}\\\\\n",
        "  \u0026\\begin{aligned}\n",
        "    \\beta_{rc}\n",
        "    \u0026\\sim \\text{MultivariateNormal}(\\text{loc}=0_{D_r}, \\text{scale}=\\Sigma_r^{1/2})\n",
        "  \\end{aligned}\n",
        "\\end{aligned}\\\\\\\\\n",
        "\\text{for } \u0026 i = 1 \\ldots N:  \\hspace{2.45cm}\\text{# for each sample}\\\\\n",
        "\u0026\\begin{aligned}\n",
        "  \u0026\\eta_i = \\underbrace{\\vphantom{\\sum_{r=1}^R}x_i^\\top\\omega}_\\text{fixed-effects} + \\underbrace{\\sum_{r=1}^R z_{r,i}^\\top \\beta_{r,C_r(i) }}_\\text{random-effects} \\\\\n",
        "  \u0026Y_i|x_i,\\omega,\\{z_{r,i} , \\beta_r\\}_{r=1}^R \\sim \\text{Distribution}(\\text{mean}= g^{-1}(\\eta_i))\n",
        "\\end{aligned}\n",
        "\\end{align}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3gZmFJXAHwfy"
      },
      "source": [
        "where:\n",
        "\n",
        "$$\n",
        "\\begin{align}\n",
        "R \u0026= \\text{number of random-effect groups}\\\\\n",
        "|C_r| \u0026= \\text{number of categories for group $r$}\\\\\n",
        "N \u0026= \\text{number of training samples}\\\\\n",
        "x_i,\\omega \u0026\\in \\mathbb{R}^{D_0}\\\\\n",
        "D_0 \u0026= \\text{number of fixed-effects}\\\\\n",
        "C_r(i) \u0026= \\text{category (under group $r$) of the $i$th sample}\\\\\n",
        "z_{r,i} \u0026\\in \\mathbb{R}^{D_r}\\\\\n",
        "D_r \u0026= \\text{number of random-effects associated with group $r$}\\\\\n",
        "\\Sigma_{r} \u0026\\in \\{S\\in\\mathbb{R}^{D_r \\times D_r} : S \\succ 0 \\}\\\\\n",
        "\\eta_i\\mapsto g^{-1}(\\eta_i) \u0026= \\mu_i, \\text{inverse link function}\\\\\n",
        "\\text{Distribution} \u0026=\\text{some distribution parameterizable solely by its mean}\n",
        "\\end{align}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5AYonR45P1Hr"
      },
      "source": [
        "In other words, this says that every category of each group is associated with a sample, $\\beta_{rc}$,  from a multivariate normal. Although the $\\beta_{rc}$ draws are always independent, they are only indentically distributed for a group $r$: notice there is exactly one $\\Sigma_r$ for each $r\\in\\{1,\\ldots,R\\}$.\n",
        "\n",
        "When affinely combined with a sample's group's features ($z_{r,i}$), the result is sample-specific noise on the $i$-th predicted linear response (which is otherwise $x_i^\\top\\omega$)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "__dP1MdYKda0"
      },
      "source": [
        "When we estimate $\\{\\Sigma_r:r\\in\\{1,\\ldots,R\\}\\}$ we're essentially estimating the amount of noise a random-effect group carries which would otherwise drown out the signal present in $x_i^\\top\\omega$."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0EZXZzlYSbM7"
      },
      "source": [
        "There are a variety of options for the $\\text{Distribution}$ and [inverse link function](https://en.wikipedia.org/wiki/Generalized_linear_model#Link_function), $g^{-1}$. Common choices are:\n",
        "- $Y_i\\sim\\text{Normal}(\\text{mean}=\\eta_i, \\text{scale}=\\sigma)$,\n",
        "- $Y_i\\sim\\text{Binomial}(\\text{mean}=n_i \\cdot \\text{sigmoid}(\\eta_i), \\text{total_count}=n_i)$, and, \n",
        "- $Y_i\\sim\\text{Poisson}(\\text{mean}=\\exp(\\eta_i))$.\n",
        "\n",
        "For more possibilities, see the [`tfp.glm`](https://github.com/tensorflow/probability/tree/master/tensorflow_probability/python/glm) module."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XajrojApx5cR"
      },
      "source": [
        "## Variational Inference"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fIQn1mlYAUzx"
      },
      "source": [
        "Unfortunately, finding the maximum likelihood estimates of the parameters $\\beta,\\{\\Sigma_r\\}_r^R$ entails a non-analytical integral. To circumvent this problem, we instead \n",
        "1. Define a parameterized family of distributions (the \"surrogate density\"), denoted $q_{\\lambda}$ in the appendix.\n",
        "2. Find parameters $\\lambda$ so that $q_{\\lambda}$ is close to our true target denstiy.\n",
        "\n",
        "The family of distributions will be independent Gaussians of the proper dimensions, and by \"close to our target density\", we will mean \"minimizing the [Kullback-Leibler divergence](https://en.wikipedia.org/wiki/Kullback%E2%80%93Leibler_divergence)\". See, for example [Section 2.2 of \"Variational Inference: A Review for Statisticians\"](https://arxiv.org/abs/1601.00670) for a well-written derivation and motivation. In particular, it shows that minimizing the K-L divergence is equivalent to minimizing the negative evidence lower bound (ELBO)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Nu8B7ylx3UdL"
      },
      "source": [
        "## Toy Problem"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vDmAfghTJcLo"
      },
      "source": [
        "[Gelman et al.'s (2007) \"radon dataset\"](http://www.stat.columbia.edu/~gelman/arm/) is a dataset sometimes used to demonstrate approaches for regression. (E.g., this closely related [PyMC3 blog post](http://twiecki.github.io/blog/2014/03/17/bayesian-glms-3/).) The radon dataset contains indoor measurements of Radon taken throughout the United States. [Radon](https://en.wikipedia.org/wiki/Radon) is naturally ocurring radioactive gas which is [toxic](http://www.radon.com/radon_facts/) in high concentrations.\n",
        "\n",
        "For our demonstration, let's suppose we're interested in validating the hypothesis that Radon levels are higher in households containing a basement. We also suspect Radon concentration is related to soil-type, i.e., geography matters.\n",
        "\n",
        "To frame this as an ML problem, we'll try to predict log-radon levels based on a linear function of the floor on which the reading was taken.  We'll also use the county as a random-effect and in so doing account for variances due to geography. In other words, we'll use a [generalized linear mixed-effect model](https://en.wikipedia.org/wiki/Generalized_linear_mixed_model)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_zr34b0IBqgY"
      },
      "outputs": [],
      "source": [
        "%matplotlib inline\n",
        "%config InlineBackend.figure_format = 'retina'\n",
        "\n",
        "from __future__ import absolute_import\n",
        "from __future__ import division\n",
        "from __future__ import print_function\n",
        "\n",
        "import os\n",
        "from six.moves import urllib\n",
        "\n",
        "import matplotlib.pyplot as plt; plt.style.use('ggplot')\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns; sns.set_context('notebook')\n",
        "import tensorflow_datasets as tfds\n",
        "\n",
        "import tensorflow.compat.v2 as tf\n",
        "tf.enable_v2_behavior()\n",
        "\n",
        "import tensorflow_probability as tfp\n",
        "tfd = tfp.distributions\n",
        "tfb = tfp.bijectors"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WkKB-97-sipM"
      },
      "source": [
        "We will also do a quick check for availablility of a GPU:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 35
        },
        "id": "gWCdTCR9snIQ",
        "outputId": "5ed94af3-242e-4b6d-c1c8-58784e2fb044"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "We'll just use the CPU for this run.\n"
          ]
        }
      ],
      "source": [
        "if tf.test.gpu_device_name() != '/device:GPU:0':\n",
        "  print(\"We'll just use the CPU for this run.\")\n",
        "else:\n",
        "  print('Huzzah! Found GPU: {}'.format(tf.test.gpu_device_name()))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UzepxbtrpHpD"
      },
      "source": [
        "### Obtain Dataset:\n",
        "\n",
        "We load the dataset from TensorFlow datasets and do some light preprocessing."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 196
        },
        "id": "uCadtPD6jXfh",
        "outputId": "e805d0b7-cd48-4d6e-af33-b0619805bcbf"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "\u003cdiv\u003e\n",
              "\u003cstyle scoped\u003e\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "\u003c/style\u003e\n",
              "\u003ctable border=\"1\" class=\"dataframe\"\u003e\n",
              "  \u003cthead\u003e\n",
              "    \u003ctr style=\"text-align: right;\"\u003e\n",
              "      \u003cth\u003e\u003c/th\u003e\n",
              "      \u003cth\u003elog_radon\u003c/th\u003e\n",
              "      \u003cth\u003efloor\u003c/th\u003e\n",
              "      \u003cth\u003ecounty\u003c/th\u003e\n",
              "      \u003cth\u003ecounty_code\u003c/th\u003e\n",
              "    \u003c/tr\u003e\n",
              "  \u003c/thead\u003e\n",
              "  \u003ctbody\u003e\n",
              "    \u003ctr\u003e\n",
              "      \u003cth\u003e0\u003c/th\u003e\n",
              "      \u003ctd\u003e0.788457\u003c/td\u003e\n",
              "      \u003ctd\u003e1\u003c/td\u003e\n",
              "      \u003ctd\u003eAitkin\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "    \u003c/tr\u003e\n",
              "    \u003ctr\u003e\n",
              "      \u003cth\u003e1\u003c/th\u003e\n",
              "      \u003ctd\u003e0.788457\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "      \u003ctd\u003eAitkin\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "    \u003c/tr\u003e\n",
              "    \u003ctr\u003e\n",
              "      \u003cth\u003e2\u003c/th\u003e\n",
              "      \u003ctd\u003e1.064711\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "      \u003ctd\u003eAitkin\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "    \u003c/tr\u003e\n",
              "    \u003ctr\u003e\n",
              "      \u003cth\u003e3\u003c/th\u003e\n",
              "      \u003ctd\u003e0.000000\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "      \u003ctd\u003eAitkin\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "    \u003c/tr\u003e\n",
              "    \u003ctr\u003e\n",
              "      \u003cth\u003e4\u003c/th\u003e\n",
              "      \u003ctd\u003e1.131402\u003c/td\u003e\n",
              "      \u003ctd\u003e0\u003c/td\u003e\n",
              "      \u003ctd\u003eAnoka\u003c/td\u003e\n",
              "      \u003ctd\u003e1\u003c/td\u003e\n",
              "    \u003c/tr\u003e\n",
              "  \u003c/tbody\u003e\n",
              "\u003c/table\u003e\n",
              "\u003c/div\u003e"
            ],
            "text/plain": [
              "   log_radon  floor  county  county_code\n",
              "0   0.788457      1  Aitkin            0\n",
              "1   0.788457      0  Aitkin            0\n",
              "2   1.064711      0  Aitkin            0\n",
              "3   0.000000      0  Aitkin            0\n",
              "4   1.131402      0   Anoka            1"
            ]
          },
          "execution_count": 0,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "def load_and_preprocess_radon_dataset(state='MN'):\n",
        "  \"\"\"Load the Radon dataset from TensorFlow Datasets and preprocess it.\n",
        "  \n",
        "  Following the examples in \"Bayesian Data Analysis\" (Gelman, 2007), we filter\n",
        "  to Minnesota data and preprocess to obtain the following features:\n",
        "  - `county`: Name of county in which the measurement was taken.\n",
        "  - `floor`: Floor of house (0 for basement, 1 for first floor) on which the\n",
        "    measurement was taken.\n",
        "\n",
        "  The target variable is `log_radon`, the log of the Radon measurement in the\n",
        "  house.\n",
        "  \"\"\"\n",
        "  ds = tfds.load('radon', split='train')\n",
        "  radon_data = tfds.as_dataframe(ds)\n",
        "  radon_data.rename(lambda s: s[9:] if s.startswith('feat') else s, axis=1, inplace=True)\n",
        "  df = radon_data[radon_data.state==state.encode()].copy()\n",
        "\n",
        "  df['radon'] = df.activity.apply(lambda x: x if x \u003e 0. else 0.1)\n",
        "  # Make county names look nice. \n",
        "  df['county'] = df.county.apply(lambda s: s.decode()).str.strip().str.title()\n",
        "  # Remap categories to start from 0 and end at max(category).\n",
        "  df['county'] = df.county.astype(pd.api.types.CategoricalDtype())\n",
        "  df['county_code'] = df.county.cat.codes\n",
        "  # Radon levels are all positive, but log levels are unconstrained\n",
        "  df['log_radon'] = df['radon'].apply(np.log)\n",
        "\n",
        "  # Drop columns we won't use and tidy the index \n",
        "  columns_to_keep = ['log_radon', 'floor', 'county', 'county_code']\n",
        "  df = df[columns_to_keep].reset_index(drop=True)\n",
        " \n",
        "  return df\n",
        "\n",
        "df = load_and_preprocess_radon_dataset()\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_OxaVNnjYZyL"
      },
      "source": [
        "### Specializing the GLMM Family"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "niha5M54Yjf-"
      },
      "source": [
        "In this section, we specialize the GLMM family to the task of predicting radon levels. To do this, we first consider the fixed-effect special case of a GLMM:\n",
        "$$\n",
        "\\mathbb{E}[\\log(\\text{radon}_j)] = c + \\text{floor_effect}_j\n",
        "$$\n",
        "\n",
        "This model posits that the log radon in observation $j$ is (in expectation) governed by the floor the $j$th reading is taken on, plus some constant intercept. In pseudocode, we might write \n",
        "\n",
        "    def estimate_log_radon(floor):\n",
        "        return intercept + floor_effect[floor]\n",
        "\n",
        "there's a weight learned for every floor and a universal `intercept` term. Looking at the radon measurements from floor 0 and 1, it looks like this might be a good start:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 313
        },
        "id": "YwzykNvJgfJo",
        "outputId": "c5f3166d-0ca6-4e62-e3ef-bf10bcc07a86"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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VXVlw5cqVCjf0qiwgIEC8kd6OHTsUXsVQWlqKHTt2KGxHV1cX/fv3B1B+I01p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\n",
            "text/plain": [
              "\u003cFigure size 1200x400 with 2 Axes\u003e"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 296,
              "width": 729
            },
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, (ax1, ax2) = plt.subplots(ncols=2, figsize=(12, 4))\n",
        "df.groupby('floor')['log_radon'].plot(kind='density', ax=ax1);\n",
        "ax1.set_xlabel('Measured log(radon)')\n",
        "ax1.legend(title='Floor')\n",
        "\n",
        "df['floor'].value_counts().plot(kind='bar', ax=ax2)\n",
        "ax2.set_xlabel('Floor where radon was measured')\n",
        "ax2.set_ylabel('Count')\n",
        "fig.suptitle(\"Distribution of log radon and floors in the dataset\");"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8MqU1SefgRy5"
      },
      "source": [
        "To make the model a little more sophisticated, including something about geography is probably even better: radon is part of the decay chain of uranium, which may be present in the ground, so geography seems key to account for.\n",
        "\n",
        "$$\n",
        "\\mathbb{E}[\\log(\\text{radon}_j)] = c + \\text{floor_effect}_j + \\text{county_effect}_j\n",
        "$$\n",
        "\n",
        "Again, in pseudocode, we have\n",
        "\n",
        "    def estimate_log_radon(floor, county):\n",
        "        return intercept + floor_effect[floor] + county_effect[county]\n",
        "   \n",
        "the same as before except with a county-specific weight."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rcddRr2Ug1cH"
      },
      "source": [
        "Given a sufficiently large training set, this is a reasonable model.  However, given our data from Minnesota, we see that there's there's a large number of counties with a small number of measurements. For example, 39 out of 85 counties have fewer than five observations. \n",
        "\n",
        "This motivates sharing statistical strength between all our observations, in a way that converges to the above model as the number of observations per county increases."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 438
        },
        "id": "15f4k6gQg40_",
        "outputId": "2d9e07c6-0d5d-48e3-f67c-2386eaa9cb86"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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cI7GF3E4Z27dvx8aNG9Gh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\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            "text/plain": [
              "\u003cFigure size 2200x500 with 1 Axes\u003e"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 421,
              "width": 1291
            },
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(22, 5));\n",
        "county_freq = df['county'].value_counts()\n",
        "county_freq.plot(kind='bar', ax=ax)\n",
        "ax.set_xlabel('County')\n",
        "ax.set_ylabel('Number of readings');"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VxtwlODcdJZe"
      },
      "source": [
        "If we fit this model, the `county_effect` vector would likely end up memorizing the results for counties which had only a few training samples, perhaps overfitting and leading to poor generalization.\n",
        "\n",
        "GLMM's offer a happy middle to the above two GLMs.  We might consider fitting\n",
        "\n",
        "$$\n",
        "\\log(\\text{radon}_j) \\sim c + \\text{floor_effect}_j + \\mathcal{N}(\\text{county_effect}_j, \\text{county_scale})\n",
        "$$\n",
        "\n",
        "This model is the same as the first, but we have fixed our likelihood to be a normal distribution, and will share the variance across all counties through the (single) variable `county_scale`.  In pseudocode,\n",
        "\n",
        "    def estimate_log_radon(floor, county):\n",
        "        county_mean = county_effect[county]\n",
        "        random_effect = np.random.normal() * county_scale + county_mean\n",
        "        return intercept + floor_effect[floor] + random_effect\n",
        "\n",
        "We will infer the joint distribution over `county_scale`, `county_mean`, and the `random_effect` using our observed data. The global `county_scale` allows us to share statistical strength across counties: those with many observations provide a hit at the variance of counties with few observations. Furthermore, as we gather more data, this model will converge to the model without a pooled scale variable - even with this dataset, we will come to similar conclusions about the most observed counties with either model."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QjvAR2-ZYgxP"
      },
      "source": [
        "## Experiment"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bioH0_7ZfC4Z"
      },
      "source": [
        "We'll now try to fit the above GLMM using variational inference in TensorFlow. First we'll split the data into features and labels."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "AFFj4KrwfPMg"
      },
      "outputs": [],
      "source": [
        "features = df[['county_code', 'floor']].astype(int)\n",
        "labels = df[['log_radon']].astype(np.float32).values.flatten()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZWvgUUAbGgkc"
      },
      "source": [
        "### Specify Model"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ujtDCBCcCu1q"
      },
      "outputs": [],
      "source": [
        "def make_joint_distribution_coroutine(floor, county, n_counties, n_floors):\n",
        "\n",
        "  def model():\n",
        "    county_scale = yield tfd.HalfNormal(scale=1., name='scale_prior')\n",
        "    intercept = yield tfd.Normal(loc=0., scale=1., name='intercept')\n",
        "    floor_weight = yield tfd.Normal(loc=0., scale=1., name='floor_weight')\n",
        "    county_prior = yield tfd.Normal(loc=tf.zeros(n_counties),\n",
        "                                    scale=county_scale,\n",
        "                                    name='county_prior')\n",
        "    random_effect = tf.gather(county_prior, county, axis=-1)\n",
        "\n",
        "    fixed_effect = intercept + floor_weight * floor\n",
        "    linear_response = fixed_effect + random_effect\n",
        "    yield tfd.Normal(loc=linear_response, scale=1., name='likelihood')\n",
        "  return tfd.JointDistributionCoroutineAutoBatched(model)\n",
        "\n",
        "joint = make_joint_distribution_coroutine(\n",
        "    features.floor.values, features.county_code.values, df.county.nunique(),\n",
        "    df.floor.nunique())\n",
        "\n",
        "# Define a closure over the joint distribution \n",
        "# to condition on the observed labels.\n",
        "def target_log_prob_fn(*args):\n",
        "  return joint.log_prob(*args, likelihood=labels)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8cd1whNpMPwL"
      },
      "source": [
        "### Specify surrogate posterior"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UZ5WAja5ejQg"
      },
      "source": [
        "We now put together a surrogate family $q_{\\lambda}$, where the parameters $\\lambda$ are trainable. In this case, our family is independent multivariate normal distributions, one for each parameter, and $\\lambda = \\{(\\mu_j, \\sigma_j)\\}$, where $j$ indexes the four parameters. \n",
        "\n",
        "The method we use to fit the surrogate family uses `tf.Variables`. We also use `tfp.util.TransformedVariable` along with `Softplus` to constrain the (trainable) scale parameters to be positive. Additionally, we apply `Softplus` to the entire `scale_prior`, which is a positive parameter.\n",
        "\n",
        "We initialize these trainable variables with a bit of jitter to aid in optimization."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ov8PwoebKn2T"
      },
      "outputs": [],
      "source": [
        "# Initialize locations and scales randomly with `tf.Variable`s and \n",
        "# `tfp.util.TransformedVariable`s.\n",
        "_init_loc = lambda shape=(): tf.Variable(\n",
        "    tf.random.uniform(shape, minval=-2., maxval=2.))\n",
        "_init_scale = lambda shape=(): tfp.util.TransformedVariable(\n",
        "    initial_value=tf.random.uniform(shape, minval=0.01, maxval=1.),\n",
        "    bijector=tfb.Softplus())\n",
        "n_counties = df.county.nunique()\n",
        "\n",
        "surrogate_posterior = tfd.JointDistributionSequentialAutoBatched([\n",
        "  tfb.Softplus()(tfd.Normal(_init_loc(), _init_scale())),           # scale_prior\n",
        "  tfd.Normal(_init_loc(), _init_scale()),                           # intercept\n",
        "  tfd.Normal(_init_loc(), _init_scale()),                           # floor_weight\n",
        "  tfd.Normal(_init_loc([n_counties]), _init_scale([n_counties]))])  # county_prior"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a8IlctaL_cvE"
      },
      "source": [
        "Note that this cell can be replaced with [`tfp.experimental.vi.build_factored_surrogate_posterior`](https://www.tensorflow.org/probability/api_docs/python/tfp/experimental/vi/build_factored_surrogate_posterior?version=nightly), as in:\n",
        "\n",
        "```python\n",
        "surrogate_posterior = tfp.experimental.vi.build_factored_surrogate_posterior(\n",
        "  event_shape=joint.event_shape_tensor()[:-1],\n",
        "  constraining_bijectors=[tfb.Softplus(), None, None, None])\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yhtN7BOoXRDb"
      },
      "source": [
        "### Results"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QZU99LcO5pcb"
      },
      "source": [
        "Recall that our goal is to define a tractable parameterized family of distributions, and then select parameters so that we have a tractable distribution that is close to our target distribution. \n",
        "\n",
        "We have built the surrogate distribution above, and can use [`tfp.vi.fit_surrogate_posterior`](https://www.tensorflow.org/probability/api_docs/python/tfp/vi/fit_surrogate_posterior), which accepts an optimizer and a given number of steps to find the parameters for the surrogate model minimizing the negative ELBO (which corresonds to minimizing the Kullback-Liebler divergence between the surrogate and the target distribution). \n",
        "\n",
        "The return value is the negative ELBO at each step, and the distributions in `surrogate_posterior` will have been updated with the parameters found by the optimizer."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ow-XvCiJczNr"
      },
      "outputs": [],
      "source": [
        "optimizer = tf.optimizers.Adam(learning_rate=1e-2)\n",
        "\n",
        "losses = tfp.vi.fit_surrogate_posterior(\n",
        "    target_log_prob_fn, \n",
        "    surrogate_posterior,\n",
        "    optimizer=optimizer,\n",
        "    num_steps=3000, \n",
        "    seed=42,\n",
        "    sample_size=2)\n",
        "\n",
        "(scale_prior_, \n",
        " intercept_, \n",
        " floor_weight_, \n",
        " county_weights_), _ = surrogate_posterior.sample_distributions()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 71
        },
        "id": "sn43cNdHXe8J",
        "outputId": "78b6d9bc-94a0-4ea0-aaf8-b6843dda43a9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "        intercept (mean):  tf.Tensor(1.4352839, shape=(), dtype=float32)\n",
            "     floor_weight (mean):  tf.Tensor(-0.6701997, shape=(), dtype=float32)\n",
            " scale_prior (approx. mean):  tf.Tensor(0.28682157, shape=(), dtype=float32)\n"
          ]
        }
      ],
      "source": [
        "print('        intercept (mean): ', intercept_.mean())\n",
        "print('     floor_weight (mean): ', floor_weight_.mean())\n",
        "print(' scale_prior (approx. mean): ', tf.reduce_mean(scale_prior_.sample(10000)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 245
        },
        "id": "4ItwhsHUm0hF",
        "outputId": "10bfc60e-3565-46c6-eca9-452823f573b4"
      },
      "outputs": [
        {
          "data": {
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gQYN0+vRpeXt7KywsTPXr1y8yLj8/X3Xq1NFDDz2kbt26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\nVtLhcjCbzd0eRtHR0aE33nhDZrNZY8aM0S9+8Qt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            "text/plain": [
              "\u003cFigure size 1000x300 with 1 Axes\u003e"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 228,
              "width": 628
            },
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(10, 3))\n",
        "ax.plot(losses, 'k-')\n",
        "ax.set(xlabel=\"Iteration\",\n",
        "       ylabel=\"Loss (ELBO)\",\n",
        "       title=\"Loss during training\",\n",
        "       ylim=0);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZkAWIRuUWPee"
      },
      "source": [
        "We can plot the estimated mean county effects, along with the uncertainty of that mean. We have ordered this by number of observations, with the largest on the left. Notice that the uncertainty is small for the counties with many observations, but is larger for the counties that have only one or two observations."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 435
        },
        "id": "F5AEDIXQHZMT",
        "outputId": "d250f948-f585-4314-b1df-0a653ee30f28"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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HHtEjjzyy6naXX345wVAAAGDN1jLVytkNhEeP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\n3/mO7r777rxUCkB5c8KIBwAoB4VMPQ17c3Lq3EIiqxrOxjNv+eIaCgB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7B+jIyMRH19/bzlmiN+Uu58z549BZfdF1gZxRLsCQAUvrwFQ/3Df/gPY9OmTfGlL30pX4cEAFgx\nMvUUtmLL3KWkC8WmpKQkWlpactq6u7sjmUxGJpPJac9kMpFMJqOnpyenfd++fcvOTMXGtlLlH4HC\n5/sH1odiKXcOAACsX3kLhrrrrrviX/yLfxFf+cpX4sknn4yXXnopX4cGNjBPigArRaaewlZsmbuU\ndKEYtba2zgk26enpiZqampxSljU1NXNuRCcSiWhtbV3N5bKBCHKA4ub7B1bezTxUUkzlzgEAgPUr\nb1cIf/3Xfz0iIjZv3hxf/epX46tf/Wps27YttmzZMu+YTZs2xWc/+9l8LYEiNBP0Ul1dHRER6XR6\nLZcDQBGRqSe/8v2dfTOZu06cOJFznPr6+ptaSz7MlHSZCfCaKemyUMkIJV0odIlEInp7e6OpqSnn\nZtfk5GTO7+H1SktLo7e3V9YeAJbF9w/cvPHx8QXLiu/cuTNaWlpuGHz4ZuYrd97R0ZFzTnfp0qXo\n7OyM7u7u2baZcucLZYAk/1yDBwCgGOUtM9TLL78cL7/8crz22muzbZcvX55tv9F/skcBAGtFpp7C\nVmyZu5R0oVjV1dXFwMDAom+SJRKJGBgYiLq6uhVeGQDFzPcPLN/IyEjU19cv+GDG2NhYdHV1xZ49\ne5ZUuq7Yyp0DAMBiqXZUePJ2N+Xf/tt/m69DAQCsOJl6ClsxZu5qbW2No0eP5jwl3dPTE0eOHImG\nhoaora2N0dHRGBoayvmcRSjpQmGrq6uL4eHh6Ovrm/ff0Kqqqti3b9+ysgsAwI34/oGlGxkZib17\n984pYTefiYmJaGpqWnQw4XLLnR85cmT2HGim3HkhZPgFAADWr7wFQ9199935OhQAwIqbydTzxhsn\n3d3dkc1mo6OjIyoqKmbbM5lMdHZ2ytSziubL3LVQqbxCz9ylpAvFrLKyMtra2ua9GX327Fn/XgKQ\nd75/YPHGx8fjwIEDcwKhysrKorGxcfbhjMHBwZyHM6ampmL//v0xPDwclZWVC85RbOXOAQCA9Stv\nZfIAANabGz0h3tPTEzU1NdHc3BwHDx6M5ubmqKmpmRMIJVPPyprJ3DVjJnPXQtZD5i4lXdio3IgG\nYC34/oGf6Ovry8lSG/F6Cbt0Oh39/f1x6NCh6O/vj3Q6HclkMqffxMRE9PX1vekcxVbuHAAAWL8E\nQwEAG9ZMpp7S0tKc9plMPU888UScOHFiTskymXpW3kzmrjfq7u6OZDIZmUwmpz2TyUQymVw3mbtm\nSrq0t7fP26eqqira29vj1KlTAqHgBlKpVKRSqchms5HNZme3AQCYa3p6Oo4dO5bTlkwmo6ura07m\npvLy8ujq6opHH300p/348eMxPT294DzFWO4cAABYn/J2d+jkyZPLGvfRj340X0sAAFiymUw9+/fv\nn/OU7I3MBFAJUFl5ra2tcfTo0ZyfS09PTxw5ciQaGhpmyzgMDQ3NCVgr9MxdSrowYyaAp7q6OiIi\n0un0Wi4HAIAidPr06RgbG5vdLisri46OjgXHdHR0xJEjR2bPtS5evBhnzpxZsHxdMZY7BwAA1qe8\n3WH54he/uKxxgqEAgLU2k6mnr69v3uCUqqqq2Ldv3w1L67EyZgLPmpqaYmpqarZ9JnPXfIohc5dA\nKAAAIF8uXLiQs93Y2LhggFJEREVFRTQ0NOSce124cGHBYKiZcuczgVcz5c7nO8+OWB/lzgFgrXmY\nDmDp8naX5QMf+EBs2rRp3v2Tk5Px/PPPx/j4eGzbti3+3t/7e/maGgDgpsnUU5hk7gIAALg5V65c\nydmura1d1Ljr+12+fHnB/jPlzt94Xt3d3R3ZbDY6OjqioqJitj2TyURnZ+e6KXcOAACsL3k7q/jE\nJz6xqH5//ud/Hk8++WRs3rw5Pv7xj+dregCAFeVi7NqRuQsAAGD5tm7dmrM9Ojq6qHHX99u2bdub\njinmcucAAMD6sep39T7wgQ/Eq6++Gv/5P//nuOuuuxZMqwsAABEydwEAACzXjh07crYHBwfj0qVL\nC5bKy2QyMTQ0tOBxbmQty50rIQQAAMzYvBaT7tmzJzZv3hxf+cpX1mJ6mCOVSkUqlYpsNhvZbHZ2\nGwBYHwRCAQAA3Nju3btj+/bts9uTk5PR2dm54JjOzs6czE1VVVWxa9euRc03U+58sYFNiUQiBgYG\nlDsHAADyZk2Cod761rfGLbfcEt/73vfWYnoAAAAAANgQSkpKoqWlJaetu7s7kslkZDKZnPZMJhPJ\nZDJ6enpy2vft27ekh1Bmyp23t7fP26eqqira29vj1KlTAqFYdzxgDYXN7ygAa/II/UsvvRRXr16N\nLVu2rMX0AAAAAACwYbS2tsbRo0djYmJitq2npyeOHDkSDQ0NUVtbG6OjozE0NJSTESri9cxNra2t\nS55TuXMAAGCtrPqZRiaTiT/4gz+IiIg777xztacHACho09PTLgazbs08YVddXR0REel0ei2XAwAA\n/FgikYje3t5oamqKqamp2fbJyck4ceLEvONKS0ujt7d30SXvlsK5LwAUFtf2gGKSt7ONz3/+8wvu\nv3btWkxMTMRzzz0X09PTsXnz5vjlX/7lfE2fN+l0Ok6ePBnPPvts/OAHP4iKioq4995746Mf/Wjc\ndtttSz7W008/Hf/7f//vuHjxYkxMTERJSUm8/e1vj/e9733x4Q9/2AkfAGww4+Pj0dfXN+/+nTt3\nRktLS7S2tq7IxWYACo+LjQDAaqirq4uBgYHYv39/Toao+cwEUClhBwAArDd5i8Q5derUovvedttt\nceDAgfjZn/3ZfE2fF+fPn4/HH388XnvttaitrY2//bf/dnz3u9+Nr3zlK/GNb3wjfud3fmf24vRi\n/M7v/E5MTEzEW97ylrjzzjvjzjvvjEuXLsVf/uVfxoULF+LP//zPo6OjI7Zt27aCrwoAKBQjIyNx\n4MCBBS86j42NRVdXVxw9etRFZwAAAPKqrq4uhoeHo6+vb97ydVVVVbFv3z4P6QAAAOtW3oKhPvrR\njy64/2/8jb8RZWVlcfvtt8ddd90VmzdvztfUeTE1NRWf+cxn4rXXXosDBw7E/fffP7uvr68vvvzl\nL8fv//7vx+/+7u/Gpk2bFnXM6urqePDBB+N973tflJaWzra/9NJL8Xu/93sxOjoaX/jCF+LXf/3X\n8/56AIDCMjIyEnv37s0pR7CQiYmJaGpqioGBAQFRAAAA5E1lZWW0tbXNGwx19uxZFQ0AAIB1LW9n\nNA888EC+DrUmhoeHI5PJxD333JMTCBUR0dLSEiMjIzE6Ohrf+ta34ud+7ucWdczHHnvshu1ve9vb\n4mMf+1g89thj8fWvfz0+/vGPO7kEgCI2Pj4eBw4cmBMIVVZWFo2NjVFbWxujo6MxODgYk5OTs/un\npqZi//79MTw8HJWVlau9bADIq+npaee+C1AuEYBC4fsagJVSbOc9xfZ6AIpJYaVnWkMjIyMREbF7\n9+45+zZv3hzvf//7c/rdrDvuuCMiIq5duxY/+MEP8nJMAKAw9fX1zSmNl0wmI51OR39/fxw6dCj6\n+/sjnU5HMpnM6TcxMRF9fX2ruVwAWJbx8fE4fPjwvPt37twZhw8fXrBcLAAAAADAzVrRYKjXXnst\nXnnllXjllVfitddeW8mpbtro6GhERNx555033D/T/sILL+RlvrGxsYh4/Smbbdu25eWYAEDhmZ6e\njmPHjuW0JZPJ6OrqivLy8pz28vLy6OrqikcffTSn/fjx4zE9Pb3iawWA5RoZGYn6+vp5y+1EvH4e\n3NXVFXv27Ilz586t4uoAAAAAgI1kUzabzebzgJcvX44//dM/ja9//etx8eLFmDn8pk2boqqqKt73\nvvfFRz7ykYIKAJqcnIyHHnooIiK+8IUvRFlZ2Zw+o6Oj8Vu/9Vtx6623xh/90R/d9Jyf+cxn4mtf\n+1rcd9990d7evqgxw8PDMTw8vKi+Dz300Gz2KTaeTZs23bA9n7/uqzHHaiq210Nh83krbPn++Tz1\n1FPxkY98ZHa7rKws0un0nECoN8pkMlFTU5NTMu+pp56KD3/4w8taQzEptt+fYns9FK7V+qwV22e6\n2F7PSvna174WH/rQh+Lq1auLHrNly5b46le/Gu9973uXPa/P9fIU2+tZLcX2vhXb70+xzVNMiu1n\nU2yfAe8bq8nnYHm8b8tTbP++Fds8UGyfafMUNq+nsOdZSXkt/v3cc8/Ff/gP/yEymcycfdlsNtLp\ndJw8eTL+7M/+LH7zN38z/tbf+lv5nH7ZpqamZv//lltuuWGf0tLSiIglXdydz/DwcHzta1+LW265\nJf7JP/knix730ksvxfnz5xfV98qVK8tdHgCQR//n//yfnO3GxsYFA6EiIioqKqKhoSFOnDiRcxzB\nUAAUmpdffjkaGxvnnCuXlZVFY2Nj1NbWxujoaAwODuYE+V69ejUaGhri/Pnz8TM/8zOrvWwAAAAA\noIjlLRgqk8nE448/HleuXImtW7fGL/7iL8bP/uzPRmVlZUREjI+PxzPPPBN/9md/FplMJp544ono\n7u6OioqKm5772LFjy0qx/9hjj0Uikbjp+ZfimWeeiSeffDI2bdoUH/vYx6K6unrRY9/2trfF3Xff\nvai+W7dujYiIV199NcbHx5e11sWYWX86nV6xOcyTP6sx34svvhglJXmNs4yI4nvPiu2zZp788Hkr\nrHmut9z5rh9XW1u7qHHX90ulUjf1mv18lsfrMU8xvZYbWa351vtn+nrr/fXkc57Dhw/HK6+8ktOW\nTCajo6MjJ/j30qVL0dnZGd3d3bNtr7zySnz605+Otra2m17HG63W58G5z+Ksx8/1Uqz39+166/17\noZjm8btjn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wp/f3916dLF4n1eu8TCwYMHy+y0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\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mzJiBqVOnCsyf+ev/qampaG9vx7hx47Bs2TKJ3MSHKwPXwVxdXVVWH5HUMUNPTw+mpqZy\nndeLL76ISZMm4datWygoKEBjYyN4PB5oNBpcXFwwZ84cmdMN1OUmrKuri+3bt+PcuXOIi4sb5Jxv\naGiIuXPnIiwsTKr70WcF3aqI0PXz88P777+PH374Ad9//z0WLVqEmJgYcLlcLF68mBRCicHf3x/J\nycnIzMzERx99RAiJSkpKEBkZiZycHLS3t+PFF1+UyjxBFfDnYgYGBliwYAERjyypYEOa3+0PPvhA\n4HFaWhrS0tKG3M/f31/iMUhkQ5ECO2FI6xz9LPKsH7q4uAhda+FyuWhoaCAEeZMnT4aenmxSFg6H\nI1FCVEdHh0L+1sqq/T2LkZGR1jsiqxpSDEUiEapeWFi4cCEiIyPBZDIVaj/PZrNlmsSbmJhovDNU\nZ2cn4uLihlwoAYCIiAi5xgoICACPx0NPTw+AfuFLeHg4Dhw4gLKyMuKmbMqUKRIv0ubm5iIqKgov\nvvii0OIyv9g1kLt37yIkJASrVq2S+NzVqXb+4YcfiAVgoH9CzePx0NTUhKdPn+Knn35CUVGRVA5s\nN27cAADMmzcPb775JlG8qqqqwsGDB/Gf//wHvb29sLW1RXh4OKytrWU+f6B/siiJULG+vl5krObz\nBo/HQ25uLlE06enpIawyg4OD4efnJ/MNHR9VLC5ERESoZNFn5cqVYDAYKCoqQkxMDGJiYqCjozNo\nQVaRkXWffPIJ8vLy8OjRI9y/fx/3798H0N+97OHhQcTkKSqWj2RozMzMZBIh19TUyD0ZsLGxQXh4\nOA4fPozCwkKhHeqGhob46KOPZFqw5tPV1SXRgqK5ublcTnt9fX0SiQk7OjrkEpI5OTnh3r17YLPZ\nMDIygq+vL3R0dHD69Gn09vYSoul//vkHM2fOlHkcbUWdnXavvvrqsBF45uTkgEqliuxO9/HxwY4d\nO7BlyxZcvnwZr7zyisxjRUdHIz09Hfr6+ggICIC1tbVEiyjSkpqaCnNzc2zYsEGs+I1Op6Oqqkrm\ncezs7MBgMFBdXS2yG62mpgb5+fkSCd9VybOLs6rkxIkTSju2kZERNm7ciLCwMGRmZqKsrAxtbW0A\n+uef9vb28PX1VWlTkr6+PtavX48PP/wQ586dw4YNG6Q+RllZGSIiIgSaPzgcDlEQzsjIwPHjx/HJ\nJ5/IVHTw8fFBRkYG8vPz4ebmRgjnCwsLsW7dOowcOZJwiZM1+lUUyra7nzZtGsLCwnD+/Hncvn0b\nt2/fFrod37lbExk5ciTxNwL6r3eFhYVEDHZZWRkaGhoQHx+P+Ph4uSNNVSn+4XK5OHTokMQiWVnQ\nBDGTvKgyOma4UlVVhV27doHNZg+5raQiGHXE0Q9XFi1ahJSUFHz77bd477334OHhIfA6g8HAsWPH\noKOjgwULFkh83IMHD0q8bVVVFaKiovDkyRMAkNnN8dl7Tz09Pbz++utDiqefJ44dO6aWcaV1CjMy\nMkJQUBDCwsIIl2ZpoFKpWL58udT7aTIjRozA6tWrsXz5cpSVlQkkNNjb22tcA4g4AgIC0NnZiVOn\nTuHvv/8GANIRSkI2b96MM2fO4MaNG8Q9XHV1Naqrq6Gjo4P58+djzZo1Uh+3paVFpGhR1GvNzc1S\nj9Pd3Y1Lly7h0qVLEu8j7f31wMaEhoYGGBgYiKzr6OnpgUql4oUXXsDLL78s8Rgkmok6myEHulAK\no7KyEseOHYO+vr7MzY40Go24VxIFl8tFVVWVzE3/qqj9PYu7u7tcDc3PI6QYikRmlOnSM2PGDDx5\n8gR79+5FWFgYfH19FeJ80tXVJdONrr6+Prq7u+UeX1k0NjZi165dSs2pHgidTseyZcsEnps8eTJ+\n+OEHMBgMontIGqVrdnY2ysrK8NZbbw16LTk5mRBCTZw4Ee7u7mhoaEBqair+/vtvTJkyBU5OThKN\noy61c1JSEhISEmBqaorXX38ds2bNIhYdent7ce/ePURHRyM+Ph5eXl4SF4qLi4tBp9Oxdu1aAfXy\n+PHj8dZbb2H//v3Q19fHjh07RGZjS8PEiRNRVFSEpqYmkdF+NTU1YDKZmDJlitzjaTtRUVFISEgg\nJtw2NjYICgpCYGCgQv4/VImqCnGhoaEIDQ0V6FblL9gymUzExsaCQqHAxsZGYMFWnr+nn58fUYxr\naWnBo0ePPxYoJAAAIABJREFU8OjRI+Tl5SEuLg5xcXHEIrGHh4dUAkwS2Zg0aRKSkpJQVVWF8ePH\nS7RPZWUlnjx5opDOJD8/P0RERAh0RgL/6wqdPXu23N9hU1NToS4gz1JVVSVXN7akE7/Kykq5u0lz\nc3PBYDDg5+cHKpWKV155BRcuXMCpU6eI7YyMjLBixQqZx9FW1NlpN5wWtRsaGuDp6Unc8/BFXhwO\nh1hcsLKygouLC5KSkuQSQyUnJ0NfXx9ff/21XMLHoairq4OXl9eQLmAmJiYSOTuJ4qWXXkJBQQG+\n+OILhIWFITAwkPibcTgcJCYm4ty5c+BwOFI7laqChoYGdHR0YPTo0UP+/jY3N6OlpQXGxsYaG/U2\nEEtLS5GxrOpAX18f9vb2g+IaJaG+vh779u1DR0cHfHx84OrqijNnzghs8+KLL+LUqVNIT0+XSQzl\n7+8PGxsbAbHoli1bcOzYMWRnZ6OjowOjRo3CsmXL8MILL0h9/KFQpt09ACxbtgze3t64du3aoHsQ\nFxcXvPzyy0RMvTZgaGgIb29vIvaPzWYjNjYWV69eRUdHh9xxsKps3IuLi0N6ejomTJiAN954A3Fx\ncXjw4AG+//571NbWIjExEffv38crr7wi8+/ocHE4UnZ0zHAnKioKbDYbPj4+eO211zBu3DiZxA0D\nUUcc/XBl0qRJWL16NX7//Xd89dVXhFg+PT0d69evR2trKwBgzZo1MsWKiaOhoQHnz59HYmIiuFwu\njI2NERISIpXois+RI0dgamoqkwiARPm4uLigr6+PaIwaNWoUEQPb0NBAzAsmTZqE1tZW1NfXIzY2\nFvn5+di3bx8MDAwkGicpKQmWlpZDNkOUlJSgtrZWK51g9PX1tS5KSJiQxsbGBn5+fsjIyICrqyt8\nfX1FinHEOZA/b+jq6mLNmjUIDQ1FXl4eWCwWuFwuaDQaPD09RdY3hiI7OxvZ2dlSvyYpqoyYHNhk\nzW+6kKZZn0R70WTxs62tLTZv3oxNmzbh0qVLePXVV6U+hqenJ27evInk5GTMmDFD6DZ37txBU1OT\nTAlH6qr9hYWF4bPPPsOff/6p0e7+mgQphiIRiqpcekQxsNv71KlTAkW0Z5G3k1BS5F2kUyZnz55F\nfX097OzssHTpUoUslMiCvr4+scgJ9BdX4+PjJcpcLi4uhomJidDJSWxsLADAy8sLn332GbGIduvW\nLZw4cQJ37tyRWAylrovD7du3oaenh927dw8qqI0YMQJz586Fi4sLPv30U9y6dUtiMVRLSwu8vb2F\nLizyYyHkFYoMZNasWXj06BEiIyOxadOmQV0CbDYbx48flylrezjC79pwcHBAcHAwUbh41p5ZFM+z\nFbmOjg4cHR3h6OiIpUuXgsvlory8HPn5+YRz1M2bN3Hz5k0A/fElLi4uMscU8Rk9ejT8/f2JBZ66\nujrcvHkTN27cIJzvSDGU8pk5cyaSkpJw4sQJ7Nq1a8gOCg6HQ7h3KMp1yMzMTKnXDDc3NyQmJuLa\ntWsii+CxsbGorKxEQECAzON4eXnhxo0bSEpKErlwefv2bTQ3N8tVgPPw8EBkZKTAc8uXL4etrS1S\nU1PR0dEBa2trLFq0SCFuR9oG2WmnGPT19QUaG/jFu9bWVgGnNWNjYxQVFck1VmNjI1xdXZUqhAL6\nF2clccJobGyUq1gZGBiI7Oxs3L9/H8ePH8eJEydgZmYGCoWCpqYmcLlcAP2/ofL85iiDrq4ufPbZ\nZ+jr65Mouq27uxt79uyBvr4+Dh8+rFVd35oCl8slXKqk4eLFi+jo6MC6deswf/58ABgkhho1ahTG\njRsncyejoaHhoDnj6NGj8dlnn6G7uxtsNhujR49WqPBCVXb3fOzt7fHhhx8q9JjqgsfjoaysjLiH\nfzaOS5FCMmWTkJCAESNGYNu2bTAzM0NSUhKAfhGulZUVfHx84OHhgR9//BGurq4qic4hEaSxsREZ\nGRmoqakRG2Go6Q5cBQUFGDNmDLZs2aLwTnJ1xNEPR5YsWYLx48fj/PnzxPWM7+Rla2uLsLAwhUYu\ntbW14eLFi4iLi0Nvby/09fWxcOFChISEyOxcmpycrHGxULIgaZzcswy8Fmki27dvx969e2FjY4M3\n33xTYL0d6Bdb/P7776BQKPj222/R3NyMI0eOoKioCLGxsULrOcI4fPgwgoKChhRD3bp1C3fv3tVY\nMZSsnwM+8oiH2Gw2bty4gby8PDQ2NoqNNZU0QncoZzAGgyFyG1XVyrQNU1NTkWIIaWpYgGqESuqK\nmOTHpZJoBvv27SPuXalUKvbt2yfxvhQKhRDDayt0Oh2Ojo5ITEyUSQwVEhKC+Ph4HDlyBDU1NYS7\ncl9fH1gsFlJSUhAdHQ0jIyOZGtTUVfsrKipCcHAwoqOjkZWVBR8fH0IwLYygoCCZxhlOkGIoEqGo\nyqVHEUgrUhJnYSkKWSwsVUlOTg7MzMywZ88epcR3SAuXy0VCQgIuXryIuro6iW4k//nnH6GLyGw2\nG8XFxQD6hUwDF7Vfeukl/Pnnn1LFB6lL7cxkMocsqNnY2MDV1VWqSEYOhyPSwpz/vCJVyDNnzkRK\nSgrS09Px4YcfEpPF4uJifPfdd3j06BE6Ojowffp00hlqAKWlpVIXfMjJqyA6OjpwcHCAg4MDIY5i\nMpnIzMxEbGwsampqUFNTI7cYCvifOxQ/Om9glBXZ0awafH194eLigoKCAuzZswfr16+HnZ2d0G2Z\nTCZOnjyJ4uJiODs7w9fXV66xW1pakJ+fj6qqKrS1tUFHRwfGxsawtbWFq6urXC5NAwkNDUVKSgpO\nnz6NtLQ0BAUFESIhFouF+Ph4FBYWYsSIERIvZApj6dKliI+Px9GjR1FdXU1M/DgcDp4+fYqUlBRc\nuHABo0aNkqmjeCimTZumsVE+qkRTOu3YbDZKSkrQ2tqKMWPGqPSeXRGYm5sL/CbzF+keP34s8Dmr\nqKiQ+57YxMREJTEx1tbWKC8vR09Pj0jRTnt7O5hMptwi6Y0bN8LJyQlXrlwBi8USWJyxsLDA4sWL\nCQGLJpGYmIi2tja88cYbElmXW1pa4tVXX8Vvv/2GpKQkIp5NEfT29oossAOQO6pVE6ipqUFBQYFE\nUa7PkpOTg3Hjxg35OaLRaHJFwIrCwMBAYieEoVCH3f1wYKC7qzDx07PR14q6rwL6722ExeAo6v+p\nuroakydPHjS/5vF4xMLzrFmzcPXqVVy+fFlhzunaiKqiYwZy9epVnD17FhwOZ8htNV0MxeFw4ODg\noNDfGHXE0Q93+K53bW1tAk4jslw/RdHd3Y2YmBhcuXIFnZ2d0NHRwdy5c/Haa6/JvdZnbm6u0Y2/\nkiJtnJy2cPHiRVRWViIyMlLo/aW3tzcmTJiA//f//h/+/PNPrFq1Chs3bsTHH3+MtLQ0udYQtBF5\nPgfyrL82NDRg9+7dAnNURaBKV6DnGVlqWID6hEqqQFiTpDITgkjE8+jRIwD9DWIDHz9PGBkZydzs\nSKfTsXnzZhw6dAjR0dFEalBSUhLR2GJgYIDw8HC57qtUXfs7evQo8e+SkpIh68mkGIoUQ5GIQFUu\nPaI4d+6cXPuLQxE2lZoG3z5b2UKoxsZG5Obmorm5GWZmZvD09Bw0yU9KSkJ0dDRqa2sBSF4QaG1t\nhYuLy6Dny8rKwOPxYGxsTDgd8dHR0YGdnR0KCgpkfEf/g8vlEhbDxsbGChc89PT0SLSoZGxsjJ6e\nHoWOrWjCw8Pxxx9/4Pr163j48CEAEEIUXV1dLFy4kMws//8hJ6+Kp6urC4WFhUR3eVlZGeFmIc8x\nGQwGEY9XVVUl8Lq1tTXc3d3h4eEBd3d3ucYikZxNmzZh586dKC4uxtatW2FrawsHBwfiutLS0oLS\n0lIias7CwgLh4eEyj9fe3o5ff/2ViBwQhq6uLoKDg7F69Wq5r7k2NjYIDw/H4cOHUVhYiMLCwkHb\nGBoa4qOPPpLLmYZOp2PLli04ePAgLl68iIsXLwIA7t+/j/v37xPjbNq0SeviO7WVf/3rX7CyslLp\nmGw2G7/88guSkpLQ19cHoH8yzL9nv3HjBi5evIjNmzcPut/SJBwdHZGWlobe3l6MGDECXl5eAIDT\np0/DyMgIVCoVN2/eRE1NDXx8fOQay9vbGzk5OeByuUoVwk6bNg1nz57F2bNn8fbbbwvdJioqCl1d\nXZg+fbrc482fPx/z588nOtV4PJ7CC3eKJjMzE3p6epg3b57E+8ydOxdRUVFIT0+XWwzFZrPx559/\nIjU1Ff/884/I7bRByP6su/NAurq6UF1djcTERPT09IjsnBZHS0vLkM4CQL8zLn9BdyjEnbM4KBQK\nDA0NMWbMGNjZ2Un1PVZ31DWPx0NOTg4eP36M1tZWODo6EoWJtrY2sNlsjBkzRmNE+iUlJQLR1nzx\nEz9memC0tTJEphwOB9HR0bhx48Ygpw9DQ0MsWLAAr732mtzCkt7eXoH1Db6Alc1mC7wvW1tbidec\n/vzzTwDAyy+/DGNjY+KxpGhqLIKyo2OEHfPXX3/FyJEjsWTJEuTn5+Px48dYv349amtrkZaWBhaL\nhQULFmDChAkKHVsZWFlZES5DikIdcfTPCyYmJiIdX2Wlr68PcXFxuHjxIlpaWgAA06dPx4oVKxTm\n2OHt7Y0HDx6IFeRrA8N13S05ORlubm5i19XNzMzg5uaGlJQUrFq1CnQ6HRMnTiTWSBSJvC61ykaW\nNRMWi4Wenh65RIFRUVFoaGjAxIkTERISorC0juEstlEFyqxhDTfUnRBEIp6dO3cC+N+1jv9YUajT\nVU8SOjs7UVxcLNcavJeXFw4ePIiYmBhkZ2eDxWKBx+PB3NwcPj4+CAkJkajpThjqugcJDAwU6QJF\nIhxSDEUiFFW59Kia4TpBGjNmDFHYUhbXrl3DmTNnBLrs9PT0sHbtWsyZMwd1dXWIjIwkVKiGhoZY\nsmQJFi9eLNHxKRQKOjo6Bj1fVlYGACKjB0aNGiXze29vb8f169eRkZGBiooKovjNF1n5+flh3rx5\nCulWpVKpKCkpEegafRYej4fS0lKpi1FDuZ2Je12WGxZdXV288cYbCAkJQX5+Purq6sDlckGn0+Hh\n4fHcTh6EQU5e5aerqwsFBQVEd7kw8ROdToerqyvc3NxkGmPdunUCvyPm5uaE+MnDw0OjC8TDGVNT\nU+zfvx8nT55EcnIyKisrhS7qUSgUzJgxA+vWrZO5k7m5uRmff/45ampqAPQLUydMmABTU1PweDy0\ntbWhvLwcHR0duH37NoqKirB79265rw9+fn6IiIjArVu3UFBQIOBk4OrqitmzZyukAOHh4YFDhw7h\nypUryMrKEuhc9vb2RkhIiNRRLvJ2Xu7atUvm/bWdhoYGiT6rGRkZYDKZchc6u7q6sGfPHlRUVMDU\n1BQODg7IysoS2Mbb2xs///wz0tPTNVoM5ePjg/j4eGRkZGD69OmwtrbGrFmzcPfuXXz55ZfEdnp6\nelixYoVcY61YsQJZWVn4+eef8fbbbyvNAebll19GfHw8YmNjUVpaihdffBEAUF9fj5s3byIlJQUM\nBgO2trYKdTiiUqlac32rqKiAo6OjVAUYAwMDODo6gslkyjU2m83Gjh07iOuDnp4e4cw6cO6iLfe/\nAzsIxeHr6yuTo66hoSFRtBVHfX29xIVjSc9ZHKNHj0ZYWBhmz54t0fbqjLpmMpmIiIggPnNAf2MN\nXwyVlpaGEydOYOvWrRrjxMuPX9DT04O9vT0hpHB2dlZ64ZTL5eKbb75Bbm4ugP7CsKWlJXg8Hlgs\nFpqbm/HXX3+htLQU27Ztk0tAZm5uLvD55t+j8R2j+DQ3N0u8RsHvTp4xYwaMjY2Jx5KiiWIoday7\n8Zs2d+7cCUdHRxw9ehSPHz/GnDlzAPRf00+dOoW7d+9KFLeqbmbPno3ffvsNLBZL4fHS6oqjH840\nNTXhn3/+AYVCgbm5udz3V4mJiTh//jxYLBYAwNPTE6tWrVJ4JOvy5cuRmZmJw4cP491339Wae5ln\nGa7rbqJqM88yYsQIgXsTGo1GrKWLgu+GwYfFYg16jk9fXx+qq6vx6NEjODg4SHDm6uHgwYMSb1tV\nVYWoqCg8efIEQP/fTFZyc3NhZmaG3bt3K0QERSI/yq5hDTe0KSHoecTDw0PsY3lRl6seALGOevxG\nrcuXL6O5uRkBAQEyjwP0z0/Wrl1LPBZXo5UGdd2DfPDBB2oZV5shxVAkQlG3S4+yGK4TJH9/f1y5\ncgXt7e1KsbRmMBg4ffo0gP4bRGtra7DZbLBYLJw8eRIWFhY4cuQIWlpaoKuri3nz5mHZsmVSFYlp\nNBoqKioGXYj4Ih7+AvSzdHR0yFSMfvDgAY4dOya0246/GFReXo6rV69iw4YNckf8eHl5IS4uDr/9\n9htWr149aBGWy+Xi7NmzqKurw9y5c6U69lCdlaJel/eGxdjYmCjYkZAoCr74ib8YW15eLlT85OLi\nAjc3N7i5ucm9QGxgYAA3NzdCADVu3Di5jkeiOIyMjLBx40aEhYUhMzMTZWVlaGtrA9DfgWtvbw9f\nX1+5u2N/+ukn1NTUYOzYsXjrrbdERu1lZmbi9OnTePLkCU6cOIHNmzfLNS7QX0hTRSGLSqVizZo1\nWLNmjUKOJ2/30PNMdHQ0goKC4OfnJ3a7jIwM3L17V+7PR0xMDCoqKhAQEID169fDwMAAYWFhAttY\nWlrCysoKeXl5co2lbKZPnz7IHWn9+vUYO3Ys0tLS0N7eDmtra7zyyitSOz/wXdMG4uvri7i4OGRn\nZ8PDwwN0Ol3kgsmyZcukGo+PgYEBdu7ciUOHDuHx48dEYwlfBAz0Cys++eQTqQRZsrrp8NEkG+3W\n1lahjsVDwW9GkIfLly+jpqYG/v7+eOedd/Df//4XCQkJ+Pnnn9He3k4ULH19ffHee+/JNZYqENdB\nqKenByqVCnd3d5n+3kD/InlRURGamppgbm4udJuamhowmUyJhTwuLi4yL1T29PSgrq4OLS0t+Omn\nn6Sev6ja7r6hoQF79+5Fe3s7vLy84OrqiqioKIFtpk2bRohXNUUMxcfKygpOTk5wdnbG5MmTVeIg\ncevWLeTm5sLKygpvv/02vL29BV7Pzs7G6dOnkZubi1u3bknlMPcs1tbWROEUALEmdvnyZWzevBkU\nCoVo4pD0GvTqq6+CQqEQaxr8x9qMOtbdSktL4eDgIHLdSE9PD++88w6ysrIQHR2NjRs3qvgMpWP+\n/PkoKSnB3r17sW7dOnh5eSnNCU6VcfTDjZs3b+Lq1auEqwifsWPHYuHChVJHD2dlZeHs2bNEA5Cj\noyNWrVolc9PXUFy4cAGOjo548OABsrOz4eTkBDqdLtQlikKhCBQRSZSPqakpCgoKxDp39fT0oKCg\nQEBg3tHRMaSDxuHDhwUeFxQUSFTP0XaxSENDA86fP0+4gRsbGyMkJAQLFiyQ+Zj8tA5SCKUZqKKG\nNdxQd0IQiXgyMjJAp9OV5mwqz1xbXiQV9NBoNIW7kGn7fItEekgxFIlQ1OHSI4za2lrExcUR9vBT\np04l4rceP36MyspKTJ8+XSlW69pEaGgo8vPzsX//frz//vuwtrZW6PFv3LgBAJg3bx7efPNNYhJW\nVVWFgwcP4j//+Q96e3tha2uL8PBwmcZ3dXXF7du3ERsbi4ULFxLHz8nJAQCRhWkmkyl152FKSgoi\nIiLA4/Fga2uLwMBAODg4wMzMDDweDy0tLSgpKUFCQgKqqqrw/fffY+PGjTJFRfAJDQ3F/fv3cfXq\nVTx48AD+/v6wsLAAhUJBXV0d7t+/DxaLhVGjRkmV6z5c3c5Inl/Wrl07SPxEo9Hg6uoKV1dXuLu7\nK7w79tSpUxoTM0IiHEtLS+LaoGgqKyuRmZkJS0tLfP3112IXDvldT9u2bcODBw/w5MkTuSLsVMGh\nQ4dgZmaGdevWKeX4jo6OCAgIICM0lACXy1XIBD01NRXm5ubYsGEDRowYIXI7Op0+KCZUG9DV1SWi\nX+RBXEx3fX097ty5I3Z/WcVQQL9oZ9++fcjOzsbDhw8F3Nt8fHwwdepUqT8L8rrpaJIYSldXV6Cz\nV1I4HA50dXXlGjs9PR0mJibYsGED9PX1Bf4fjI2NsWDBAjg4OGDXrl1wdHQkXEg0FWV3EM6aNQuP\nHj1CZGQkNm3aNMj9ic1m4/jx4+ByuZg1a5ZEx9yzZ4/c53Xv3j0cO3YM165dk0gMpa451sWLF9He\n3o63336bKMw9K4YyNjbGuHHjpBZpKZOVK1cSjjIxMTGIiYmBjo4ObG1tCZcoV1dXpTRuxcfHw8DA\nALt27RLqxuLt7Q1bW1t8/PHHiI+Pl0sMxY9PLSkpgaOjI9zd3WFtbY309HRs2LAB5ubmqKqqAo/H\nk3ic5cuXi31MIhlsNltgjsgXD3d1dRGiPD09PTg5OSE/P18t5ygNH374IYD++4/9+/dDV1cX5ubm\nQu8FKBTKIGGDLCgjjn64wuVycejQIaSnpwMA4QgF9LtE1dbW4ueff0Zubi42b94s8VoD37XMwMAA\nCxYsIK5XQ7n88JHWlZC/1gv0i2oePXokdntSDKVapkyZgri4OBw6dAjvvvvuoHuThoYGnDp1Ci0t\nLQJNtTU1NUPG/cycOZP4PUlKSoKlpaXImGO+WH7q1KlyOV+qk7a2Nly8eBFxcXHo7e2Fvr4+Fi5c\niJCQELmilwDAwsJC6WkdJJKjihrWcGO4JgQNFw4cOICgoCC8//77g147evQonJ2d5XIQV8RcW1bE\nzbn51x4PDw/Mnz//ua//k8gPKYYiEYqqXXqEcefOHZw6dUpg4bu1tVXg3ydOnICurq7EC6nDhX37\n9g16jsfjobi4GJs3b4aFhYXIznUKhULY2EtKcXExYSU48MZn/PjxeOutt7B//37o6+tjx44dMhdD\nFy9ejPj4eJw+fRopKSkYPXo0Hj16BC6XCwcHB6GRLSUlJWhubpaqu7e1tRU//vgjAAgsMg9k3Lhx\ncHV1xdKlS3Ht2jX8+uuvOH78+JBZ7eKg0+nYvn07Dh06hPr6evz111+DtqHRaAgPD5dq8V3VXZfS\nOoEoOzeYZPjB5XKJiDC+85Osuc2SQgqhnm/4dvBr1qyRaCHM2NgYb731Fg4cOICkpCSJo7jUFSuX\nkZGBqVOnyjy2KGbOnIn09HSUlJSgrKwM3t7eCA4Ohp+fn9ziA5J+6urqFNJhWldXBy8vL7FCKKDf\nba29vV3u8RTJhg0b4O7uTlwT5HWBE8crr7yitGNLire39yBXE1kR1+HHYDAwevRorXFCNDMzE4gM\nk5Samhq5I19YLBZcXV0HdeRzuVzi/mHy5MlwcnLC7du3NV4MpWxmzpyJlJQUpKen48MPPyTmAsXF\nxfjuu+/w6NEjdHR0YPr06Sp1NQoODsbt27dRUVEh0fbqcpTOycmBtbX1kA4FNBpNbtczRcIXpHK5\nXJSVlYHBYCA/Px9FRUVgMpmIjY0FhUKBjY0NIY5ycXFRiJD6yZMncHNzExtLRaVS4ebmJrerpb+/\nP0xMTIj7RR0dHWzduhUHDx5EVVUVWlpaQKFQMH/+fIXGmpIMjYmJCTo7O4nHfOFdfX09xo8fTzzf\n29srtPFT06ivrxd43NfXJzZKRBZUEUc/XLl27RrS09NBpVIRFhYGf39/QoDH4XCQlJSEc+fOISMj\nA9euXZPaTae7uxuXLl0iIlslQRZXQlLcpBg4HA7a2towYsQIhYp+ly9fjqysLGRlZWHjxo2YPHky\nsdbf0NCAoqIi9PX1gU6nE0LasrIyNDQ0IDAwUOyxB7rjJSUlwdnZWWihXdvp7u5GTEwMrly5gs7O\nTujo6GDu3Ll47bXXFNbMFRAQgL///httbW0SR0CTKA9V1LCGG8M1Ieh5gO8Grq3zDmXMuU+ePCnX\n/u+++66CzkQ1NDY2Ii8vD01NTejt7RW5nSZGq6saUgxFIhRVuvQIo7CwED/99BMMDQ2xYsUKuLi4\nDBLweHt7w8jICBkZGc+dGEpctw6Xy0Vtbe0gm2Z5aGlpgbe3t1DBAP9mSN7FTGtra3zwwQc4duyY\ngKrc3Nyc6Ip7lps3bwIAPD09JR4nNjYWXV1dWLVqlUQ2uAsXLkRPTw+ioqJw48YNuTo1J02ahMjI\nSKSkpIDBYKCpqQk8Ho8QfkyfPn3IQqW6kaaYL28MH8nzSUREhFKL3eLgcDhITU0Fg8FAY2MjABDf\nz2nTpkkVT0SiPZSWlsLIyGjIyLKBTJkyBUZGRlIVItUVK0elUpXSqbhx40Z0dnbi/v37uHfvHh4+\nfIiHDx/C2NgYAQEBCA4OVpqNszby559/CjyuqKgY9Byfvr4+VFdXo7CwUCHFJ11dXbGTYj6NjY0q\niTSShubmZiQlJRGiRX5BWxlOgZIKG1UBj8dDdnY2qqurYWhoCG9vb6nnWOI6/MLCwuDt7a01RY9J\nkyYhKSkJVVVVAkVtcVRWVuLJkyfw9/eXa2wKhSIgSuR/R9ra2gSEVjQaDZmZmXKNpQzUEZcYHh6O\nP/74A9evX8fDhw8BgIhZ0tXVxcKFCwm3Z1ViYWGh8d3LTU1NEgmYDQwMBIQfmoKOjg4cHR3h6OhI\nxG2Vl5cTTjNFRUW4efMmMY+3traGi4uLXPFbfX19MDAwGHI7AwMDqe+H+vr6BATepqamCAgIENjG\nysoK3377LWpqatDe3o6xY8fC1NQUaWlpZKS8CrGwsBAQC/HvQe/fv09c31taWpCfn48xY8ao4xSl\n4siRIwo/pjri6Icrd+/exYgRI7B79+5Baxd6enoIDg6Gs7MztmzZgjt37kgshlK1K+HLL7+s0vGG\nG/Hx8bh+/TqYTCa4XK6Ac0dqairS0tKwcuVKmb9Hpqam2LdvH06cOIHMzEyhogNfX1+sX7+eaEy3\nt7dHVFSUVA1/ERERcrsjaRp9fX2Ii4vDxYsX0dLSAqA/bn3FihUKX28MCQlBfn4+vv76a7z//vsa\n7xy7avAnAAAgAElEQVQ+3FFFDWu4oSkJQSQkiiAuLk6u/bVFDMXj8fDLL7/g5s2bEjm5kmIoUgxF\nIgJVufSI4vLly6BQKNi+fbvQsYD+Caa1tTWqq6vlHk/b2Llzp0rH43A4Iq0I+c8r4iZyxowZcHV1\nxcOHD9HS0gI6nY6pU6eKLMw5ODhgwoQJcHd3l3iM7OxsGBsbY8mSJRLvs2TJEsTExCArK0tu2/oR\nI0YgMDBwyC4dTUWUywCXy0VDQwOxADl58mRSOEIiE+oSQpWVlRHObc9y+/ZtnDt3DuHh4VprC04i\nmpqaGpGTe1FQKBTY29vL5FSi6lg5Hx8fpKSkoKenZ5CzibyMHDkSc+bMwZw5c1BTU4N79+4hISEB\nsbGxiI2NhZ2dHYKDg+Hv768w51BtJTo6WuAxk8kEk8kUu4++vr5CJqzW1tYoLy8X+xlob28Hk8nU\nuN+4Tz/9lCjaMZlMNDY2IjExEYmJiQD6BSj8gp2bm5tWFDiB/nvruLg45Ofno6+vDzY2Npg3bx7G\njBmDlpYWfPXVVwKfDz09Paxdu/a5dR2aOXMmkpKScOLECezatWvIe0wOh4MTJ04Q+8qDubk5IZAG\n/leoLC8vF3Dxqqmp0ch7X3XEJerq6uKNN94gikN1dXXgcrmg0+nw8PCQ261LVjZs2IB33nlHLWNL\nysiRI4minThYLJZSIucUjY6ODhwcHODg4ECIo5hMJjIzMxEbG0uI5OQRQ40ZMwYFBQXgcDgiv4Mc\nDgeFhYVSXyMiIiIQHh4uUUzpwJiV1NRUREZG4uzZs1KNNxCyy1c63N3dcfHiRTQ0NIBOp8PX1xej\nRo3CX3/9hadPn4JGoyEtLQ1dXV1KcUxVNMq4n1FHHP1wpba2Fu7u7mLXLsaOHQt3d/cho+cGomxX\nQkXE6ZD088MPPyAhIQFAv1C+q6tL4HUajYbk5GRMnDgRS5culXkcc3NzbN26FQ0NDYOa9pydnYV+\nZ6V1PlfXGpyySExMxPnz58FisQD0N1CvWrVK6jUfSdm3bx/6+vpQWlqKLVu2gE6ni03rkNXxm0Qy\nVFXDGk5oQkIQCYmicXR0hI+Pz7BNA7l8+TKuX78OCoUCb29vjBs3TiHJAsMZzVutI9EIVOXSI4rH\njx/D0dFRpBCKD41Gw5MnT+QeT9vw8PBQ9ykoDTMzM4kn5vPnz5f6+HV1dXBycpLqQqirq4vJkyej\nqKhI6vGE0dDQIBD5OJAxY8ZotK3uUDnClZWVOHbsGPT19bF9+3bVnBQJiZz8888/+PLLL9He3g4a\njQZ/f3+MHTsWPB4PLBYLSUlJYLFY+PLLL3HgwAGxMRwk2gebzZZpAm9iYiKVM5S6YuWWL1+Ohw8f\n4tChQ/i///s/pX1+ra2tsWrVKqxYsQI5OTm4d+8eMjIycPr0afz++++YPn06PvroI6WMrQ28+uqr\noFAo4PF4uHDhAiZMmCDSjUxPTw9UKhVeXl4KWaibNm0azp49i7Nnz+Ltt98Wuk1UVBS6urowffp0\nucdTJL6+voQjbWdnJwoLC5Gfn4+CggKUlZXhn3/+QUJCAlGMoNPpAuIoeTrsORwOWltbYWRkJFKY\n39XVRfyGSCqE4XA4+PzzzwXmWA8fPsSdO3fw5Zdf4tSpU2AymTAxMcGYMWNQX1+PtrY2nDp1Cg4O\nDkpbyNdkfH194eLigoKCAuzZswfr16+HnZ2d0G2ZTCZOnjyJ4uJiODs7i3Q0lpSJEycSTUE6OjpE\nE0ZUVBSsra1BpVJx48YNlJeXa2Q8tDrjEo2NjUU2SjU3N4PD4ajUBUNfX1/homBFM2HCBBQXF6O5\nuVnk7//Tp0/BZDLl/myrkq6uLuL3W1Qcl6xMmTIFMTExOHLkCNavXz+oAMZms3Hy5Ek0NTUNcnUa\nirS0NBw/fhzvvfeeVPtERETI/P7ILl/ZmDlzJpqamlBfXw86nQ5DQ0P861//QmRkJFJTU4ntJkyY\ngGXLlqnxTNWHOuLohytGRkYSFZwMDQ01ynFH2+N0NAV+A9CECROwYcMGTJw4cZDD7KRJk2Bubo6s\nrCy5xFB86HS6Sppqe3p6UFdXh87OTvB4PKHbODk5Kf08ZCErKwtnz55FZWUlgP5C+KpVq5Qe8znQ\nAZzH46G+vl5okyUJiaai7oQgEvUSFhYGCoWCQ4cOwdraGmFhYRLvK08qDJfLRVJSEjIyMlBWVobW\n1lb09fXB1NQUdnZ2mDp1KgICAqSev0+YMAFMJhMlJSWor68nkgskdRjXFu7duwddXV3s2rULzs7O\n6j4drYAUQ5GIRBUuPaJgs9kSFes4HI7CFtFIxNPS0iI24kfc65pUGOju7pZJJTty5Eh0d3dLtc+R\nI0dQXV2Nd999Fw4ODsTz58+fFxlZ4eHhoXLnL0Via2uLzZs3Y9OmTbh06RJeffVVdZ8SCcmQXLp0\nCe3t7ViwYAFWr149qKC9fPly/Pbbb4iNjcWlS5ewbt06NZ0piTLo6uqSqTiqr68v1XVBXbFyZ8+e\nhZ2dHTIzM/HRRx/B0dERdDpd6HumUChyuTMA/Z2oPj4+8PHxQVtbG44ePYqHDx8SCynPKwOdJS9c\nuAA7Ozu8/vrrKhn75ZdfRnx8PGJjY1FaWkqIE+rr63Hz5k0ivtfW1lajiyMjR44kPlvA/4rrDAYD\n+fn5KCsrQ0NDA+Lj4xEfHy93XO+1a9dw5swZ/Pvf/xY5vykpKcHevXuxZs0aLFq0SKLjXr9+HY8f\nP4aJiQnmzJkDMzMzlJSUIDExEf/973+Rm5uLkJAQrFy5khDQnTlzBjExMYiNjdWaaDtFs2nTJuzc\nuRPFxcXYunUrbG1t4eDgQLgMtbS0oLS0lCiAWFhYIDw8XO5xvb29kZKSgtzcXHh7e8Pe3h7e3t7I\nzs7GRx99RPwfAdDI+15NjUs8cOAASktLyUjtZ5g1axby8vJw+PBhhIeHD3J/6urqwk8//QQul4tZ\ns2ap6SyHhh/HxWAwRIqf6HQ6IcqQh5CQENy/fx8pKSnIzs7GlClTYGFhAQqFgrq6OmRmZqKzsxM0\nGg0hISFSHXv06NG4e/cujIyMsGbNmiG35ztCcblcqZyoB0J2+cqGjY3NINHa1KlTERERgczMTLS3\nt2PcuHHw8/Mbth3iQ6HOOPrhhoeHh0SOdEVFRQpZIyfRLG7fvg1DQ0N8+umnYmsXlpaWWiOKYbFY\n+OWXX5CVlSW2ziLv/EqZ7N+/H0B/LO6CBQuIOS8/6msoZHVI3r17t0z7kSiP4VLDUhXqTggiUT+i\nxK/K2q+kpAQRERGEg99AGhsb0djYiKysLERHR+P9998fZL7CYrFEupl+8803qKysxN27d5GUlIQr\nV67gypUrcHBwQHBwMGbOnCnSPU6bYLFYcHZ2JoVQUkCKoUjEomyXHlGMHj1a6I/hs9TU1JAOHWLg\n8XiIj48Hk8nEmDFjMHv2bJFitqHIzs5Gdna21K9r2kTJxMREpslofX29VI5N/KLWlClTBIRQA3lW\nPd/Z2YlHjx6htLRU5D7aAJ1Oh6OjIxITEzWyKERC8izZ2dmwsLDAW2+9JdQ9QVdXF2vWrEFmZiay\nsrLUcIYkmoq0Ez91xMrduXOH+Dc/JkYc8oqhAAi8t6amJgBQmvOINnLu3DmVjmdgYICdO3fi0KFD\nePz4MeFIxC9SA/2Lv5988olGxnyJwtDQEN7e3kRUGZvNRmxsLK5evYqOjg6ZF2b4ZGRkgEajiS1i\nubu7g0qlIj09XWIxVEpKCnR1dbFv3z6BouTYsWMRHR0NKpWKFStWENcjCoWCVatW4f79+0N+f4cz\npqam2L9/P06ePInk5GRUVlYSwqeBUCgUzJgxA+vWrVNIjJi/vz+cnZ0F5gEff/wxTp8+jbS0NLDZ\nbIwdOxavv/46WfCUEnm/o8MRf39/JCcnEwJmvlCopKQEkZGRyMnJQXt7O1588UWR7oLqgC9+4js/\nlZeXCxU/ubi4EI40iorjMjExwe7duxEREYGysjIkJSUN2sbBwQEbN26U+jdh586d2LNnD65evQoj\nIyOxLkx8IVRfXx+WLFmC1atXS/1eALLLV9FQqVTMnTtX3achMykpKUhNTcXTp09FOrVQKBQcPnx4\nyGORQijFsWLFCmzbtg2HDx/GO++8M2jexnf07OnpwcqVK9V0liTKorKyEpMnTx6yHmFubo7S0lKJ\nj9vQ0ACg/3dLR0eHeCwpsjq0NDY2YseOHWhtbcXo0aPB4/HQ2toKBwcH1NbWoqOjA0C/05IyHa0V\nRXd3Ny5duoRLly5JvI88tYvnUTyj6QyXGpaqUHdCEMnQiBPwDSX+G+o36tn1SWWvVzIYDHz55Zfg\ncDgwNTXF9OnTBzW5lZSUICUlBU1NTdi/fz82bdpEzH1Pnz6NUaNGiZ2X2dra4q233sKbb76JzMxM\n3Lt3D1lZWTh16hR+/fVX+Pn5YdasWfD09JQoDl0TMTIyIv5mJJKhPavdJM8VTk5OSE1NFSsKyc3N\nxdOnTzW6g11VXL58GRcuXMDWrVsFOiu/+eYbgcL93bt38eWXX8LAwECq4w8ny0t7e3tkZWWhoaFB\n4vdVX1+PkpISwolAEvhW7KGhoSK3+eGHHwQeFxYWYvfu3UhOTtZqMRTQf0FWVKwgCYmyaWxsxAsv\nvCD2BlhHRweOjo548OCBCs+MRFUMNXkURnNzs1xjqipWbsOGDXIfQxLYbDbhesWPDzQ2NsbLL7+M\n4ODg5zLaayi4XC7a29sB9P+tlOlUQKVSsW/fPmRnZ+Phw4dgsVjgcrmg0Wjw8fHB1KlTtW4RgMfj\noaysjCi+FxYWorOzk3hdXgFebW2tRG5t48ePR0VFhcTHra6uhpOT06CiZFBQEKKjo2FnZzfos6Cj\nowM7Ozvk5eVJPM5wxMjICBs3bkRYWBgyMzNRVlaGtrY2AP2CCHt7e/j6+iq04KunpzfoeCNHjsR7\n772H9957DzweT+u+OySazebNm3HmzBncuHED6enpAPp/N6qrq6Gjo4P58+dL5FKkStauXTtI/ESj\n0eDq6gpXV1e4u7srTPwkjLFjx+Lrr78m3AIbGxvB4/GIc5BVVGRra4tt27Zh7969iI6OJu5rnkVR\nQiiA7PIl6YfL5eLQoUPEbwCJZpGQkABfX18kJCTg4cOH8PLyIn7jWCwWcnNz0d3djcDAQCLKeSBk\nvKV209fXJ9G6ent7u1TioQ8++EAgquiDDz6QeF95RByXLl1Ca2srQkNDsXLlShw9ehTx8fH46quv\nAIAoIBsaGmL79u0yjaEKhlPtgkR2yM+BbKgzIYhkaMQJ/MS9pmkCv66uLnz33XfgcDhYuHAhVq5c\nKTS1ICgoCG+++SbOnj2L2NhYHD16FIcOHcIff/yBu3fvSuyyr6Ojg6lTp2Lq1KlobW1FQkIC4uPj\nkZKSgpSUFJibm2POnDlaeV/m7u4uleCahBRDkWgoixYtQkpKCr799lu899578PDwEHidwWDg2LFj\n0NHRwYIFC9R0lppDVlYW9PX14eLiQjyXm5uLrKwsmJubIzAwEHl5eSgtLcXdu3eFLuCJ41nRjjYz\nY8YMZGZm4tixY9i2bduQDggcDgfHjh0Dl8vFjBkzJB6nqKgIo0ePFmolKgpnZ2dYWFgIqPC1kc7O\nThQXF8PIyEjdp0JCIhH6+vqEIEEcHR0dMsWpkWg+Q3WOKRNlx8opUzTO4/GQm5tLCLl6enqI9xMc\nHAw/Pz+tchpSBe3t7bh+/ToyMjJQUVFBFI/5Yhc/Pz/MmzdPYc5gzzLQSUnb4HK5KCsrIxytnhU/\n2drawsXFhSi+y/s3bG9vl8hFxNjYWKJrCB9+XNOz8J8Tdd6mpqbo7e2VeJzhjKWlJRYuXKiUY2dk\nZIBOp0scW0oKoUgUDd+RNDQ0FHl5eQLiVU9PT5ibm6v7FAfB5XJBpVKJ2Ds3NzdYWlqq/DyUISKa\nNGkStm7div379+OXX37ByJEjERQURLyempqKiIgIIhpPHiEUQHb5yguDwSDiaFtbWxEQEIB//etf\nAPrv9xkMBhYuXAgzMzM1n6l44uLikJ6ejgkTJuCNN95AXFwcHjx4gO+//x61tbVITEzE/fv38cor\nr2D27NnqPt3njujoaOLfPT09IkVrwoRQACmG0nbodDqqqqrEbsPlclFVVSWVQJ8v4uDPn1Ul6sjJ\nyQGVSkVYWJjQ1318fLBjxw5s2bIFly9fxiuvvKKS85KW4VS7IJEd8nMgO+pKCCIRz3AS+N24cQOt\nra1YtGjRkM09+vr6ePvtt0GhUHDt2jV8+umnaG5uhqmpqUzxjKampli8eDEWL16M8vJynDt3DllZ\nWbh+/bpW3peFhYXhs88+w59//qmV568OyOoEiUYyadIkrF69Gr///ju++uorQlSRnp6O9evXo7W1\nFQCwZs0a2NraqvNUNYLa2lrY2NgIdJHznYk+/vhjODs7o7u7G//617+QlJQktRhqODFz5kxcuXIF\neXl52L17N9555x2RueBlZWU4deoUSkpKMGHCBMycOVPicZ4+fSqTu9PYsWPBZDKl3k9ViLNp7urq\nQnV1NS5fvozm5mYEBASo8MxISGTHzs4ODAYD1dXVIp1EampqkJ+fj0mTJqn47EiUjSZMLBUZKydt\nIV9WoqKikJCQgMbGRgCAjY0NgoKCEBgYqPEFJnXx4MEDHDt2DGw2e9BrXC4X5eXlKC8vx9WrV7Fh\nwwZMmzZNDWepWZSUlIDBYCA/Px9FRUWE+ElHRwcTJkwgxE8uLi4YNWqUQsc2MTFBXV3dkNvV1dVJ\nLQAX5gKmaGewodzu5LVTH64cOHAAQUFBeP/99we9dvToUTg7O5POxCQqwdTUVGQzDpfLRXx8PGbN\nmqXisxJORESE2iK4JP1e3rt3DwwGQ+h3eyjc3d3x8ccf4+DBg/jxxx9hZGSEqVOnIiUlBZGRkQoT\nQvHHIrt8ZeP8+fO4cOGCwHMDY+X09PTw999/g0qlavyaWEJCAkaMGIFt27bBzMyMiH+0srKClZUV\nfHx84OHhgR9//BGurq4YM2aMms/4+eLVV1/VWjF0Wlqa1I7IgORxjM8DXl5euH79OhISEhAYGCh0\nm7i4ODQ3N0t1nX5WxKEqUUdDQwM8PT2JuQj/s83hcAhhlpWVFVxcXJCUlKSxYih1wmazcePGDeTl\n5aGxsVFkAwv5PSIhIZGW4STwy8zMhKGhIVasWCHxPitWrMCdO3fQ3NwMc3Nz/Pvf/5Z5vby7uxsp\nKSm4d+8eCgsLAUCk+5mmER8fP+i54OBgREdHIysrCz4+PqDT6SLvTwc28zyvkGIoEo1lyZIlGD9+\nPM6fP08sBvGLR7a2tggLCyOyQp932traBFyhgP7INTMzM6Iz0sDAAE5OTigrK1PHKWoMFAoFn3zy\nCXbt2oWSkhJs27YN48ePh6Ojo0A2bXFxMZ48eQKgv1C+detWqRY72Gy2SDcBf39/kUVqExMToUVS\nTUFSm2YajYZVq1Yp+WxISBTDSy+9hIKCAnzxxRcICwtDYGAgsejD4XCQmJiIc+fOgcPhkJ23wxB1\nTSyVFSunqkL+pUuXAPTbYwcHB8PR0RFAf+wkXyAlDlFC5OFKSkoKIiIiwOPxYGtri8DAQDg4OMDM\nzAw8Hg8tLS0oKSlBQkICqqqq8P3332Pjxo1SuVJKApfLRVtbm1iHIU0QCPLZsWMHgP4Cpr29PSF+\ncnZ2VvqihaOjIxHFJk44L22Usqr4/PPPxb6uTXbqmgJ/AYoUQ5GoCy6Xi4SEBFy8eBF1dXUaI4ZS\nlxAKkPx7WVhYiPj4eJnEUADg5+eH999/Hz/88AO+//57LFq0CDExMeByuVi8eLFChFAA2eUrKxkZ\nGbhw4QJoNBrWrFkDV1dXrF+/XmAbNzc3mJiY4OHDhxovhqqursbkyZMHNRgMjGadNWsWrl69isuX\nL8PT01Mdp/ncsnz5cnWfgsx0dXWhq6tL3aeh1SxduhTx8fE4duwYnjx5QjSw9Pb24smTJ0hNTcVf\nf/0FY2NjrUiz0NfXF3BA58+xWltbQaVSieeNjY1RVFSk8vPTdBoaGrB7926xzcMkJCQkmspQ60bi\noFAo2LVrl8Tb19TUwMnJSarUDX5NOycnB1988YVM0esMBgP37t1DWloaurq6QKFQ4OHhgaCgIJlc\nptTB0aNHRb5WUlJC1BVEQYqhSDEUiYbDj/Joa2sTsIcfeDNO0k93dzfxbzabjZqaGrzwwgsC2xgZ\nGUkV4zFcodFo+Oabb3Dy5EmkpqaiqqpKqMUxhULBtGnT8M4778DExESqMfT19UUuMHh6eopcrOru\n7tboSCFxBVI9PT1QqVR4eHhg/vz5CndoICFRFoGBgcjOzsb9+/dx/PhxnDhxAmZmZqBQKGhqaiJi\nrGbOnEk6npHIhbpj5ZRRyC8tLZXaweB5E1q0trbixx9/BAC8/fbbQhfFx40bB1dXVyxduhTXrl3D\nr7/+iuPHj8PNzU0hcTnFxcU4f/48CgoKxAqhNPX/xsrKCk5OTnB2dsbkyZNV0r01d+5cZGRk4MCB\nA/jggw/g7u4u8HpeXh4hppwzZ45UxxbnyiTqtebmZqnG0CRRGwkJiXgaGxuRm5uL5uZmmJmZwdPT\nc9CaR1JSEqKjo1FbWwsAZJSalPT19cntwBcQEIDOzk6cOnUKf//9NwDI7QhFdvkqhtjYWOjp6WH7\n9u2wsbERug2FQoGVlRXxHdJkent7Bb7j/KIRm80WWGextbVVW9Q3iXbi7e2NkJAQdZ+GVkOj0bBl\nyxYcPHgQf//9N3E9SE5ORnJyMgBg5MiR2Lx5s1Zcq83NzQWEPHyB8+PHjwWciisqKqR2w30eiIqK\nQkNDAyZOnIiQkBCMGzcOI0eOVPdpkZCQkEiELG6RsiLOPEIcxsbG0NHRkUoIVV9fj/j4eMTHx4PF\nYgHov74FBQUhKCgINBpN6vNQJ4GBgVrrSqopaG7FnYRkACYmJlKLUZ4nLCwsUFJSAi6XCx0dHTx8\n+BA8Ho9wheLT1tYGU1NTNZ2lZmFsbIyPP/4YdXV1RNd/W1sbgP7Pm729PXx9fWXucjUzMyOcpaTh\nyZMnGh0vNJysOUlIBrJx40Y4OTnhypUrYLFYAs42FhYWWLx4MZmJTiIXwy1WjhRaSE5sbCy6urqw\natUqibqDFy5ciJ6eHkRFReHGjRtyd58XFhZi79694HA4AIBRo0ZpzQLtypUrwWAwUFRUhJiYGMTE\nxEBHRwe2traES5Srq6tMCypD4e3tjZdeegl37tzB3r17MWbMGMKOu6amhlhQ4QsZpUGcK5O416SB\nvGcjAZQflyjr4ik/8pIEuHbtGs6cOUP8RgP9TSZr167FnDlzUFdXh8jISKLb09DQEEuWLMHixYvV\ndcpayZMnT6Qu4gr7fNvY2MDPzw8ZGRlwdXWFr6+vyO+BJHGjZJevYigrK8PkyZNFCqH40Gg0VFRU\nqOisZMfc3BwtLS3EY/5cge8Yxae5uRl9fX0qPz8S7WX06NHPbRSyInF3d8d3332HK1euIDs7G3V1\ndeByuaDT6fD29sbSpUuVUmjl8XjIzs5GdXU1DA0N4e3tLfe83NHREWlpaejt7cWIESPg5eUFADh9\n+jSMjIxApVJx8+ZN1NTUaKQbrrrJzc2FmZkZdu/erTVzbBISEpJncXR0REBAgFLXp42NjdHU1CT1\nfk1NTRJrAxISEnD37l0UFBSAx+PB0NAQs2bNQnBw8KBauTYhaVoPiWhIMRSJRiCsG04anvcFoClT\npuDy5cs4dOgQPDw88Ndff0FHR2dQYaa8vBxWVlZqOkvNxNLSEgsXLlT4cSdPnoz4+HhUVlbC1tZW\non2YTCZqa2uf+88zCYm6mD9/PubPn0/EfPF4PNKNkERhDLdYOVJoITnZ2dkwNjbGkiVLJN5nyZIl\niImJQVZWltxiqOjoaCLmc8WKFVoljA8NDUVoaCi4XC7KysrAYDCQn5+PoqIiMJlMxMbGgkKhwMbG\nhhBHubi4KGwBZ8OGDbCyssKlS5dQX1+P+vp64rVRo0YhNDQUS5culeqYpJCQRJUoOy5RHlt9kn6x\nzenTpwH0i5ysra3BZrPBYrFw8uRJWFhY4MiRI2hpaYGuri7mzZuHZcuWadXvuDJ4VkBUVFQkUlTE\n5XJRXV2NsrIy+Pr6SjXOUJ9vBoMhchtJnRbJLl/F0NPTI1GRRFuEmNbW1gLNdXwB1OXLl7F582ZQ\nKBQUFBSAwWBgwoQJajrL5wf+mvULL7yAkSNHSr2GTa7xDU/MzMywevVqhcWkAgCHw0Fc3P/H3r1H\nVVXn/x9/HUBU5BagIiqKIMIBFUjznuaYzZilfW3C7PbNshpLf9pUU9lCHS2dKWdGTS2VqaZmrKy+\nlVOUTXlDxfCuIAIe8UZyUbkooBzP+f1hnJEERQTOAZ6PtVxL9/5s9gt1cc7Z+73f7++UkpKiixcv\nqlOnTho5cqTatm2rwsJCvfbaa8rKyrKtv7x4uraio6O1YcMGbd++XQMGDFBAQIBuu+02rVu3Tq++\n+mqlc40fP/5Gvr0mqaSkRNHR0RRCAWiUBg0apOTkZGVmZspkMikqKsr2wJ+zs3OdnqtLly5KTU1V\nUVFRjT/PFhUVKT09XeHh4TVaX3GtuuLae//+/dWyZUtJlScrVadiLZoeiqHgEK72NFxNNPcPlmPH\njlVycrLtlySNHj26UuvAtLQ0FRUV6bbbbrNXzGZl8ODB2rBhg+Lj4xUXF3fNNw8XL17UO++8I0ka\nOHBgQ0QE8LOvv/5aLVu21K9+9StJko+PDwVQqDeMlWt+cnJy1KNHj+saz+Ps7KzQ0FAdPHjwhs+f\nmZmpjh076oknnrjhr2UvTk5OCgkJUUhIiO6++25ZLBYdPnxYKSkpts5Ra9eu1dq1ayVduokYHh5e\nJ9/z3XffrVGjRikzM9M2QsLPz08hISG1GmtJISEaUn0X31Hcd2O+/fZbSdLIkSP10EMP2UZhHQKG\n0eEAACAASURBVDt2TAsWLNCf//xnlZeXKzAwUNOnT1dAQIA94zqMXxYinDx58pqjz7y9vXX//fdf\n13ka4v83T/nWjZtuuknZ2dnXXHf8+HG1bdu2ARLdmKioKO3Zs0eZmZkKCQlRZGSkAgIClJycrCef\nfFI33XSTjh07JqvVqpEjR9o7bpNXcc26e/fuat269XVfw27u16xRM2azWbNnz1Z6erpt286dO/XD\nDz/o1VdfVXx8vLKysuTh4aG2bdsqLy9PxcXFio+PV3BwsIKCgmp13gEDBmjAgAGVtk2aNEn+/v7a\ntm2bzp49q4CAAN1zzz0UX1ahXbt2dOgD0GhNnTpVpaWl2rx5s9avX6+dO3dq586dcnd315AhQzRs\n2LA6+9nft29f7d27V3//+981bdq0Gh3z97//XWazWbfccst1navi2nt8fHyNj+Hae9NGMRQcQnh4\neLVPw6WmpsrLy8s2lgJXatOmjebPn6+tW7eqsLDQdrHkcoWFhbrjjjsotGkgvXr1ktFoVGpqqubM\nmaPHH3+82pbtx44d08qVK5WWlqawsDBFRUU1cNrqXT43vja4QYLG4B//+IeioqJsxVBAfeDnYfN1\n/vz5Wj0p2rp16xo9uXQtVqu1xl0qGwsnJycFBwcrODjYVhyVlZWlHTt2KCEhQdnZ2crOzq6zAjAX\nF5dG3VIb1+dqo+NudKxcQ6vv4juK+25MRkaG/Pz89Oijj1YqmO3cubMeeeQRzZ8/X66urpoxY0aj\nHKlbX373u9/Zfr9s2TKFhYVV+9CXi4uLfHx8FBoaet0FrA31/zs/P1/nzp2Tl5fXNf+dCwoKVFhY\nKHd393oZwdRYRUREaP369dqzZ49txNMvbdmyRfn5+TUaWWxvgwcPloeHh220o5OTk1544QUtWLBA\nx44dU2FhoQwGg+644w4NHz7czmmbvooObhX/HnR0Q3345ptvlJ6eLg8PD40YMULe3t7KzMzUpk2b\n9M4772jv3r0aM2aM7r//fhkMBlmtVv3zn//UmjVrlJCQoMmTJ9dZFmdnZ1uHXlzdkCFD9MUXX6i4\nuLjGY5wAwJG0bt1aI0aM0IgRI5Sdna3169dr48aNSkhIUEJCgrp06aJhw4Zp8ODBN9ShePjw4Vqz\nZo22bt0qs9msxx9/vNrPPgUFBVq5cqWSk5PVrl27Bnm/a7Va6/0c9eH48eP66aefVFpaWu33QGE+\nxVBwELNmzap2X2xsrKKiour0TX1TVDH/tDr9+vVTv379GjARpk2bpldeeUUHDhzQ73//e3Xt2lXd\nunWzvWkoKiqSyWSytThu27atpk+fbsfEV7qRJ1WppkZj4enpSUtr1LuGvGHclG7kNwUeHh6VxqvV\nVF5eXp1cUA0MDFRhYeENfx1HVFZWprS0NFuHKJPJJIvFUm/nO3funKRLDyKg6bra6LgbHSsHXK6w\nsFBRUVFVdg6sGItVl6M/m4phw4bZfr969Wp179690rbGpKysTC+++KIuXryo+fPnX3P9+fPnNWvW\nLLm6umrx4sW2bmLN3d13363ExET95S9/0UMPPVTp2tf58+eVlJSkd955R66urho1apQdk1bt4sWL\nlbqJe3p6asiQIZXWdOjQQW+88Yays7N19uxZ+fv7y9PTU9u2beNaXz375XUxOrqhpKRE3377rfbv\n36/Tp0+rvLy8ynUGg0GLFy+u0dfcunWrnJ2dNXfuXPn7+9u2+/v7a/Xq1fLx8dH48eNthXgGg0ET\nJkzQ5s2blZaWVuPsTz75pCIjI2U0GhUREVHpXLh+Y8aMUUpKiubNm6fJkydX+yA0ADQGAQEBmjBh\ngsaPH689e/Zo/fr12r59u9577z198MEHGjBggKZMmVKrr+3i4qLnn39eM2fOVHJysnbt2qVevXop\nJCREXl5eki59Ps7IyNC+fftkNpvl5uam559/vsYPtXzwwQe1ytYYHTx4UMuXL680Wrs6FENRDAUA\n9cbLy0vz5s3TypUrlZSUpKysrEqz3S/Xv39/Pf744w73FAmdTNAchIWFXffYMsCRcSPfsXTr1k27\ndu1Sfn5+jV9X8/LylJmZqejo6Bs+/6hRo7Ro0SJlZWU1+tEGZWVlOnDggFJTU6stfvLz87Nd3K8L\n+/fv15o1a3TgwAFbp66WLVvKaDRq9OjRV3RjRePGe180JLPZXG1xZcV2CqGurrF3J9u0aZOKi4v1\nwAMPqH379tdc3759e40bN07vv/++EhMT6Qr0s44dO2ry5MlaunSpVqxYoZUrV0q69PdbMVbR2dlZ\nzzzzjNq1a2fPqFVauHChpk+fXqNuQ5ePy0xKStKiRYv0r3/9qz7j4Wfnzp3Tnj17lJeXpxYtWqhr\n166N6kGSjz76yN4RmoT8/HzNnDnzhjvp/9KJEyfUo0ePK4qThg4dqtWrV6tLly5XFE87OTmpS5cu\n2r9/f43PU1BQoMTERCUmJkqSfHx8FBERIaPRqMjISIf8GenI5s6dq4sXL+rQoUN67rnn5OfnJz8/\nvyp/nhsMBsXFxdkhJQBcHycnJ0VHRys6OlrFxcVaunSpdu7cqT179tzQ1w0MDNS8efP05ptvKiMj\nwzaWryohISGaMmXKdRXttmjR4obyNRYnTpzQ3LlzdeHCBYWGhqqgoEC5ubkaNGiQTp48qcOHD8ti\nsahv3762zqbNHcVQQBNz4cIF5eTkXLUtXo8ePRo4VfPl7u6uadOm6eTJk9q5c6dMJpOKi4slXeoU\nERQUpJiYGHXo0MHOSavW2C8uAzVx77336qWXXtLHH3+s3/72t7S8R6PGjXzHM3DgQO3YsUPLli3T\nSy+9dM0nmsxms5YtWyaLxVIn440HDhyo48ePa86cOYqNjVVMTEyj+X9SUfxU0fmp4gP95fz8/BQe\nHq6IiAhFRETU6QX8Tz75RKtXr75i+/nz57Vr1y7t2rVL9913n8aNG1dn54R98d4XaFxiY2M1bNiw\nSqPzqvLWW29p/fr1Dlf0vWPHDrm4uGjkyJE1Pub222/XqlWrlJycTDHUZQYNGqTOnTvr008/1Z49\ne1RaWiqLxSJXV1f17NlT9957r7p162bvmFXatm2b3n77bT311FPXdczChQvrtSMm/mvLli1avny5\nSktLK20PCgqyFUCgeVi1apXy8/MVFBSkMWPGqGPHjnXSaby0tLTK8acV26obTeTp6VltZ6qq/OEP\nf7B9tsrKytLp06e1adMmbdq0yXa+is9VERERatu2bS2+m+bj8q7bVqtVeXl5teoKDQCO5vKReWfO\nnJF06QGEG+Xv76+5c+cqJSVF27dvl8lkUlFRkaRLr2lBQUHq06cPDx5exeeff64LFy5o0qRJGjFi\nhJYuXarc3FxNnTpV0qXReUuWLNFPP/2kuXPn2jmtY6AYCmgicnNz9e6772rXrl1XvRhC1wf78Pf3\nd8h27ACkw4cP69Zbb9Wnn36qpKQk9enTR23btq127AStReHIuJHveAYNGqR///vf2r9/v2bOnKnH\nHnus2ptxJpNJ8fHxyszMVNeuXTVo0KDrPl9sbGy1++Lj4xUfH1/tfkd7n/joo49e8b7W19dXRqOx\n3p9e3rt3r1avXq0WLVpo5MiRGj58uO1cubm5WrdundauXauPP/5Y3bt3V69eveolB4Cm7Vrja6+2\nvzF1JKlP1T0EVtt1DenIkSMKCQlRq1atanxMy5YtFRISUm3X6eYsMDBQ06dPl9VqVXFxsSwWizw9\nPascRelIvLy8tG7dOrm5uenhhx++5vqKjlAWi0V33XVXAyRs3rKysrR48WJZLBa1bNlSHTp0UGlp\nqXJzc3X48GEtWLBA8+bNs3dMNJC9e/fK29tbM2fOrJMiqMtV9bOqrn9+xcTEKCYmRtKlAqyKkeMH\nDhyQyWTSqVOntHHjRm3cuFHSpQdPLi+OovCvspkzZ9o7AgDUmZKSEm3evFnr169XZmampEvNHn79\n619r2LBhCgoKqrNzVbyu4PqlpqbK399fI0aMqHJ/p06d9OKLL2rq1Kn69NNP9eCDDzZwQsdDMRTQ\nBJw+fVozZsxQUVGRvLy8ZLVaVVRUpODgYJ08eVLnzp2TdKm1oLOzs53TAoBjWbp0qe33J06c0IkT\nJ666nmIoANfDYDDo+eefV1xcnDIzM/XSSy+pc+fOCgkJkZeXl6RLN7szMjJss979/Pz0wgsvNHin\nOke7UWyxWOTj42MbexcREVGjMUJ14euvv5bBYNCLL754xRNpnTp10kMPPaTo6GjNmTNHX3/9NcVQ\nAGrlauNrr7bf0YpXHV1ZWdk1OzPaQ1FRkcLCwq77OB8fH9sNClzJYDBU20XFEb3yyiuaNWuWvvrq\nK7m5uenee++tdm1FIdTFixd11113cXOjAfz73/+WxWLRkCFD9Pjjj9uKF7OysrRgwQKZTCalpKRw\nQ6+ZKCkpUXR0dJ0XQtlD69atbWOQpEuvlWlpaUpNTVVKSopMJpPy8/O1YcMGbdiwgfceVaAwHUBj\nZ7VatXfvXq1fv17bt2/XhQsXbGPyhg0bpj59+jjk56jmrKCgwPbaLf23cLq8vNw2KtDLy0vh4eH6\n8ccf+bwgiqGAJuHzzz9XUVGRxo4dq/vvv19Lly7Vhg0b9Nprr0mSdu3apfj4eLVq1Uovv/yyndOi\nqbFardq9e7dOnDihVq1aKSoqiieF0KjceuutjMYDUK98fX31pz/9SStXrlRSUpKOHTumY8eOXbHO\nYDCof//+euyxx+Th4VGrc3300Uc3GtdhLFy4UP7+/nY5d2Zmpnr06HHV1tyRkZEKDw/nhjSAWuEz\nU/2zWCw6ceKEUlJS5OPjY+84V3B2dpbZbL7u48xmMw+6NSGBgYF66aWXNGfOHK1evdr2BP4vUQhl\nH2lpafL29taTTz5pu8EkSV27dtUjjzyi119/XQcOHKAYqplo166dLl68WC9f+2rdIKvbV1BQUGfn\nr7imGxUVJelS4VdCQoK++uornTt3zuEenAEA3JhVq1Zp48aNOn36tKRLD/4NHTpUt956q7y9ve2c\nDtX5ZVfhigLtM2fOVOqe7+rqavu3be4ohgKagD179sjHx6fasSjR0dGaMWOGnnvuOX355Ze65557\nGjghGjOz2azvvvtOKSkpunjxojp16qSRI0eqbdu2Kiws1GuvvVapRb+Li4seffTRats0Ao7m6aef\ntncEAM2Au7u7pk2bppycHO3YsUMmk0nFxcWSJA8PD3Xr1k0xMTF2K/5xRPb8uygpKZGvr+811/n4\n+CgjI6MBEgFoahhtWzu/vO5R0bHiWm699db6ilRr3t7eys7Ovu7jsrOzbd0lm6NPPvnkho6/Wucl\ne+nevbteeOEFzZ8/X++++65at25dqSNxUlKSFi5caBuNRyFUwzlz5ox69+5dqRCqQnh4uG0Nmoch\nQ4boiy++UHFxca0fXqnO1bpFXquTZF2wWq22TmepqalKS0tTaWmpbX/Hjh3r9fyNmcVi0e7du5We\nnq6ioiKFhIRo+PDhki51gTx79qz8/f0dfmwrgObl888/lyQFBwdr2LBhCgkJkXRpElFNimi6detW\nr/lQNR8fH506dcr254rX55SUFFsxlNlsVmZmZqPqllufKIaCQ6juqYcKV3syQqIlaX5+vnr16mV7\nQ13R4cRsNttaGHbo0EHh4eFKTEykGAo1ZjabNXv2bKWnp9u27dy5Uz/88INeffVVxcfHKysrSx4e\nHmrbtq3y8vJUXFys+Ph4BQcH1+kcYQAAmoL27dtr1KhRds2QlJSk5ORkFRUVydfXVwMHDmTM2y94\neXlV2b3rl44dO8bFBQBwUM7OzvLx8dEtt9xS7cNj9tS9e3clJibq2LFj6ty5c42OOXr0qI4fP67B\ngwfXczrHtXr16hs63hGLoaRLHSenTZumBQsW6K233pKbm5v69u2rrVu3atGiRRRC2YnZbJa7u3uV\n+9q0aSPp0lgSNA9jxoxRSkqK5s2bp8mTJ6tTp0518nXt0S3SYrHIZDIpNTW1yuKnwMBAhYeHy2g0\nymg08pmnGiaTSQsXLtTJkydt28xms60Yavv27Xr77bf1/PPPq0+fPvaKCQDVOnTokA4dOnRdxzA6\n1X569Oih9evXq6SkRG5uboqJiZGTk5Pee+89lZeXy8fHR99//71OnTqlQYMG2TuuQ6AYCg5h9uzZ\nV91/tacf+KF7qd2dq6ur7c8VbfKKiooqtYJ3d3fXwYMHGzwfGq9vvvlG6enp8vDw0IgRI+Tt7a3M\nzExt2rRJ77zzjvbu3asxY8bo/vvvl8FgkNVq1T//+U+tWbNGCQkJmjx5sr2/BaBK+fn5OnfunLy8\nvK7Z9rWgoECFhYVyd3evUZcQALCnvXv3atWqVerXr5/Gjh17xf6KccqXW7duncaMGaMJEyY0VEyH\nFx4ers2bN+ubb76pclSNJK1du1ZHjx7VkCFDGjgdADRfl4+DjY2N1dChQxvt585BgwYpMTFRK1as\nUFxcnO1htuqYzWatWLHCdmxz5ajFTHWhT58+mjx5spYsWaK//e1vuvPOO7VmzRpZLBaNHj2aQiig\ngVV1z+LixYs6dOiQnnvuOfn5+cnPz8/2YPLlDAaD4uLianSehuoWmZmZqdTUVKWkpOjgwYO24icn\nJyd17drVVvwUHh5uK/ZD9fLy8jR37lydO3dO0dHRMhqN+uc//1lpTb9+/RQfH6/k5GSKoQA4FMa2\nN079+vXT3r17lZqaqj59+sjHx0f33HOPPv30U8XHx9vWubm5afz48XZM6jgohoJD4IfujbnpppuU\nn59v+3PFSJH09HT179/ftv3IkSNyc3Nr8HxovLZu3SpnZ2fNnTu30qgaf39/rV69Wj4+Pho/frzt\nQ7/BYNCECRO0efNmpaWl2Ss2cFVlZWV68cUXdfHiRc2fP/+a68+fP69Zs2bJ1dVVixcvrlR8CgCO\nZvfu3TKZTHrkkUeu2LdlyxZbIVRQUJAiIyOVn5+vpKQkffHFF7r55pvVo0ePho7skMaOHatt27bp\nnXfe0bZt2zR06FC1a9dOBoNBOTk52rhxo1JSUuTi4qK7777b3nEBoFm69957G3U34piYGIWHh+vA\ngQOaNWuWJk2apC5dulS5NisrSytXrlRGRobCwsIUExPTwGkdx29/+1t7R6hXQ4YMUWlpqeLj4/XF\nF19IEh2h7OxaEwuutr+5TzNo7K727261WpWXl6e8vLwGTHRjZsyYIUlycXFRt27dbMVPYWFhtoer\nUXOfffaZzp07p4kTJ+qOO+6QpCuKodq0aaOOHTted9cVAKhvjG1vnHr27KlFixZV2nbfffcpMDBQ\nSUlJOnfunAICAnTnnXfaxuY1dxRDwSHwQ/fGhISEaNu2bSovL1eLFi3Uu3dvSdJ7770nNzc3+fj4\naO3atcrOzlZ0dLSd06IxOXHihHr06FGpEEqShg4dqtWrV6tLly5XzDt3cnJSly5dtH///oaMCtTY\npk2bVFxcrAceeEDt27e/5vr27dtr3Lhxev/995WYmGhrdQ0AjigjI0MeHh4KCwu7Yl9CQoIkqXfv\n3nrxxRdtr+H/+c9/tGLFCv3www8UQ/0sMDBQU6dO1dKlS22jI36pVatWevrppxUYGGiHhACAplAU\n8+yzz+qVV15RRkaGXnjhBQUGBio4OFheXl6SLhVZHDp0SEePHpUktWvXTtOnT7dnZIfQlDr9VvUe\no1OnTurTp4+2b98uo9GomJgYim3s6GoTC662n2kGjd/MmTPtHaFedOjQQT169FBYWJhCQ0MphKql\nPXv2qGPHjrZCqOr4+voqPT29gVIBAKRLBcA9e/ZUZGSkwsLCrtmFt7Hr379/peYo+K+m/S8PNBPR\n0dHasGGDtm/frgEDBiggIEC33Xab1q1bp1dffdW2zsXFhbZ4uC6lpaVVXiys2FbdvHhPT0+Vl5fX\nazagtnbs2CEXFxeNHDmyxsfcfvvtWrVqlZKTkymGAuDQTp06VWWXjJKSEmVkZEi61Enj8mLm4cOH\n65NPPuEC7S/069dP3bt313/+8x8dOHBAp0+fltVqla+vr8LDwzVixIhKI6kBAPaTnp6ulJQUnT59\nWpLk4+OjiIgIhYaG2jnZ1Xl6emr+/PlauXKltmzZoqNHj9oKny5nMBg0cOBATZw4Ue7u7nZI6jia\nWqffqsZwXS41NbXaNRTb1D+mGTRvTa3Y8P7771dqaqoOHjyoNWvWaM2aNXJyclJgYKCtS5TRaGz2\nrzM1VVhYqO7du19zXYsWLVRWVtYAiQAAFTIzM5WZman/+7//k6urq3r06KHIyEj16tVLQUFBVY64\nRdNEMRTQBAwYMEADBgyotG3SpEny9/fXtm3bdPbsWQUEBOiee+5R165d7RMSjdYvOz9Vtw1oLI4c\nOaKQkJDrevKtZcuWCgkJUVZWVv0FA4A6UFRUpPDw8Cu2m0wmWa1Wubu7X3FjuKKr44EDBxoqZqPh\n4+Oj++67z94xAADVyM3N1eLFi6st6A0NDdWUKVMcekSAm5ubpk6dqtjYWO3YsUMmk0nFxcWSJA8P\nD3Xr1k0xMTFXdGxurppap1+KbRwb0wyat9mzZysqKkpjxoyxd5Q6MXbsWI0dO1YWi0Umk0mpqalK\nSUnRwYMHlZWVpYSEBBkMBnXq1MlWHBUeHn7NDnzNVatWrVRYWHjNdXl5efLw8GiARADQOBw7dkzb\ntm3TzTffXO3Yc5PJpJ07d2rAgAHq2LHjdZ9j/vz52rdvn/bt26e0tDTb71etWqU2bdrIaDSqV69e\nioyMVEBAwI1+S/XmWg9OXI3BYFBcXFwdpmmcKIYCmihnZ2fbBxwAwH8VFRVVOT7qWnx8fJSZmVkP\niQCg7hgMBp07d+6K7SaTSZKqvcjQpk0bXbx4sV6zAQBQl86ePavZs2crPz9fLVu21M0332wrjsnN\nzdWOHTuUnp6uP/7xj5o/f77Dd7po3769Ro0aZe8YDq+pdfql2AZwXKmpqWrbtq29Y9Q5JycnhYSE\nKCQkRHfffbcsFosOHz6slJQUW+eotWvXau3atZKkgIAAhYeH64knnrBzcscSFBSkgwcP6syZM7rp\nppuqXJOdna2srCzdfPPNDZwOABzXt99+q++//1633XZbtWu8vLz0ySefqLi4WI8++uh1nyMoKEhB\nQUG6++67ZTablZGRYSuIOnTokJKTk5WcnCzp0n2fZcuW1fr7qU/VjcpGzVEMBTRCTz75pCIjI2U0\nGhUREcHTgahXhYWF1b7gVrevoKCgvmMBtebs7Cyz2Xzdx5nNZjk7O9dDIgCoO76+vjpy5IisVmul\nls8Vr9chISFVHnfu3Llqx982d5mZmUpNTa00esloNFb7dwkAaBhffvml8vPz1a9fP02aNOmKrgtn\nz57V8uXLtW3bNn355ZeaMGGCnZKiLtHpFwDqlpOTk4KDgxUcHGwrjsrKytKOHTuUkJCg7OxsZWdn\nUwz1C7fddpv27dunRYsW6dlnn73ifUhJSYnefvttWSyWq97wB4DmJiUlRV26dJGvr2+1a3x9fdW1\na1ft37//hs/n4uKi8PBwhYeH67777tPZs2f1+eef65tvvlF5ebntep8jCwkJ0ZAhQ+jWWAsUQwGN\nUEFBgRITE5WYmCjp0g2ZiIgIGY1GRUZGOnT7dzQ+u3fv1u7du697H+CovL29lZ2dfd3HZWdny8vL\nqx4SAUDdMRqN+v7775WQkGDrLnHs2DHt2bNHkhQTE1PlcVlZWYxp+YX8/HwtXrxYaWlpVe4PDw/X\nM888w98bANhJcnKyvL29NWXKFLVo0eKK/e7u7poyZYoOHjyo5ORkiqGaCDr9AkD9KCsrU1pamq1D\nlMlkksVisXcshzVo0CBt3bpVycnJeuaZZ2Q0GiVJGRkZ+utf/6p9+/bp3LlzGjBgAJ2hAOAyp0+f\nVu/eva+5rl27dtq3b1+dnDMrK8vWGerAgQO6cOGCJKl169a2n9+OaNCgQUpOTlZmZqZMJpOioqI0\nbNgw9enThwf3a4hiKKAR+sMf/mD7UJKVlaXTp09r06ZN2rRpk6RLFbMRERG2X02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            "text/plain": [
              "\u003cFigure size 2000x500 with 1 Axes\u003e"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 418,
              "width": 1185
            },
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "county_counts = (df.groupby(by=['county', 'county_code'], observed=True)\n",
        "                   .agg('size')\n",
        "                   .sort_values(ascending=False)\n",
        "                   .reset_index(name='count'))\n",
        "\n",
        "means = county_weights_.mean()\n",
        "stds = county_weights_.stddev()\n",
        "\n",
        "fig, ax = plt.subplots(figsize=(20, 5))\n",
        "\n",
        "for idx, row in county_counts.iterrows():\n",
        "  mid = means[row.county_code]\n",
        "  std = stds[row.county_code]\n",
        "  ax.vlines(idx, mid - std, mid + std, linewidth=3)\n",
        "  ax.plot(idx, means[row.county_code], 'ko', mfc='w', mew=2, ms=7)\n",
        "\n",
        "ax.set(\n",
        "    xticks=np.arange(len(county_counts)),\n",
        "    xlim=(-1, len(county_counts)),\n",
        "    ylabel=\"County effect\",\n",
        "    title=r\"Estimates of county effects on log radon levels. (mean $\\pm$ 1 std. dev.)\",\n",
        ")\n",
        "ax.set_xticklabels(county_counts.county, rotation=90);"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mB0pTr-XWztv"
      },
      "source": [
        "Indeed, we can see this more directly by plotting the log-number of observations against the estimated standard deviation, and see the relationship is approximately linear."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 476
        },
        "id": "3P1YgFBxQzyt",
        "outputId": "7fd7cd82-c403-45bb-8a9a-6ca4e890917f"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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cv3690TY5iSF/8S2qZs2amSz38fEBACQlJRmUnz17FgDQunVrs1+GX3311WLFkleDBg1M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\nQMxMaVDmxnrJmBADjczSZRkX4jg1daG/mz4+DTj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KTuXkyiz+qpwvfyVJq/uc4RqtxGse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            "text/plain": [
              "\u003cFigure size 1000x700 with 1 Axes\u003e"
            ]
          },
          "metadata": {
            "image/png": {
              "height": 459,
              "width": 632
            },
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(10, 7))\n",
        "ax.plot(np.log1p(county_counts['count']), stds.numpy()[county_counts.county_code], 'o')\n",
        "ax.set(\n",
        "    ylabel='Posterior std. deviation',\n",
        "    xlabel='County log-count',\n",
        "    title='Having more observations generally\\nlowers estimation uncertainty'\n",
        ");"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AxhvAIeFs2cL"
      },
      "source": [
        "\n",
        "## Comparing to `lme4` in R"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 17
        },
        "id": "hvRDd7T-s7qY",
        "outputId": "e2bcc435-8e9d-4fe4-844c-7bdfb01a005b"
      },
      "outputs": [
        {
          "data": {
            "application/javascript": [
              "window[\"145908fc-b587-11ea-8f99-dd0ce85532c4\"] = colab.output.setWordWrap(true);\n",
              "//# sourceURL=js_6c08a75ff3"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e9b0\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"1468a9c4-b587-11ea-8f99-dd0ce85532c4\"] = jQuery(\"\u003cdiv class=id_660846384 style=\\\"margin-right:10px; display:flex;align-items:center;margin-top:10px;\\\"\u003e\u003cspan style=\\\"margin-right: 3px;\\\"\u003e\u003c/span\u003e\u003c/div\u003e\");\n",
              "//# sourceURL=js_4a5d666dd7"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e780\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"1468f2da-b587-11ea-8f99-dd0ce85532c4\"] = jQuery(\"#output-footer\");\n",
              "//# sourceURL=js_451d1c15ce"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e780\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"1469151c-b587-11ea-8f99-dd0ce85532c4\"] = window[\"1468a9c4-b587-11ea-8f99-dd0ce85532c4\"].appendTo(window[\"1468f2da-b587-11ea-8f99-dd0ce85532c4\"]);\n",
              "//# sourceURL=js_17add669ba"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90bce1dfd0\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"1469304c-b587-11ea-8f99-dd0ce85532c4\"] = jQuery(\".id_660846384 span\");\n",
              "//# sourceURL=js_02736ccbaf"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e780\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"146950a4-b587-11ea-8f99-dd0ce85532c4\"] = window[\"1469304c-b587-11ea-8f99-dd0ce85532c4\"].text(\"\u003e\");\n",
              "//# sourceURL=js_9cc51e6da0"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e780\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"14795454-b587-11ea-8f99-dd0ce85532c4\"] = jQuery(\".id_660846384\");\n",
              "//# sourceURL=js_0a346bc667"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e780\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "application/javascript": [
              "window[\"14798bc2-b587-11ea-8f99-dd0ce85532c4\"] = window[\"14795454-b587-11ea-8f99-dd0ce85532c4\"].remove();\n",
              "//# sourceURL=js_17ae9904b3"
            ],
            "text/plain": [
              "\u003cIPython.core.display.Javascript at 0x7f90b888e780\u003e"
            ]
          },
          "metadata": {
            "tags": []
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "%%shell\n",
        "exit  # Trick to make this block not execute.\n",
        "\n",
        "radon = read.csv('srrs2.dat', header = TRUE)\n",
        "radon = radon[radon$state=='MN',]\n",
        "radon$radon = ifelse(radon$activity==0., 0.1, radon$activity)\n",
        "radon$log_radon = log(radon$radon)\n",
        "\n",
        "# install.packages('lme4')\n",
        "library(lme4)\n",
        "fit \u003c- lmer(log_radon ~ 1 + floor + (1 | county), data=radon)\n",
        "fit\n",
        "\n",
        "# Linear mixed model fit by REML ['lmerMod']\n",
        "# Formula: log_radon ~ 1 + floor + (1 | county)\n",
        "#    Data: radon\n",
        "# REML criterion at convergence: 2171.305\n",
        "# Random effects:\n",
        "#  Groups   Name        Std.Dev.\n",
        "#  county   (Intercept) 0.3282\n",
        "#  Residual             0.7556\n",
        "# Number of obs: 919, groups:  county, 85\n",
        "# Fixed Effects:\n",
        "# (Intercept)        floor\n",
        "#       1.462       -0.693"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n5IqiHERv91u"
      },
      "source": [
        "The following table summarizes the results."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "height": 71
        },
        "id": "D0sUh3NNuqlw",
        "outputId": "3c817b06-2928-45b9-81bf-650c5d39c69d"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "      intercept   floor     scale\n",
            "lme4   1.462000 -0.6930  0.328200\n",
            "vi     1.435284 -0.6702  0.287251\n"
          ]
        }
      ],
      "source": [
        "print(pd.DataFrame(data=dict(intercept=[1.462, tf.reduce_mean(intercept_.mean()).numpy()],\n",
        "                             floor=[-0.693, tf.reduce_mean(floor_weight_.mean()).numpy()],\n",
        "                             scale=[0.3282, tf.reduce_mean(scale_prior_.sample(10000)).numpy()]),\n",
        "                   index=['lme4', 'vi']))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nVjHJxVdwBXb"
      },
      "source": [
        "This table indicates the VI results are within ~10% of `lme4`'s.  This is somewhat surprising since:\n",
        "- `lme4` is based on [Laplace's method](https://www.jstatsoft.org/article/view/v067i01/) (not VI),\n",
        "- no effort was made in this colab to actually converge,\n",
        "- minimal effort was made to tune hyperparameters,\n",
        "- no effort was taken regularize or preprocess the data (eg, center features, etc.)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ApP0PtwYN_ah"
      },
      "source": [
        "## Conclusion"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eIFHW00tOJwo"
      },
      "source": [
        "In this colab we described Generalized Linear Mixed-effects Models and showed how to use variational inference to fit them using TensorFlow Probability. Although the toy problem only had a few hundred training samples, the techniques used here are identical to what is needed at scale."
      ]
    }
  ],
  "metadata": {
    "colab": {
      "collapsed_sections": [],
      "name": "Linear_Mixed_Effects_Model_Variational_Inference.ipynb",
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}
